Role Description GroundTruth is looking for a Data Engineering Manager with strong expertise in designing and building scalable data platforms and pipelines to join our team. The Data Engineering Team is responsible for the core data infrastructure that powers our audience platform. As an Engineering Manager on our Audience Engineering team, you will build solutions that add new data capabilities and analytical depth to our platform while managing sophisticated AWS-native data services. - Architect Scalable Pipelines: Oversee the design and deployment of large-scale distributed data processing jobs using PySpark on Amazon EMR clusters and serverless AWS Glue ETL jobs. - Coach and mentor engineers—supporting growth in technical skills (particularly Python and Spark optimization), data modeling best practices, and career progression. - Partner with stakeholders and engineering leadership to evaluate, plan, and deliver data-first projects across advertising systems, analytics services, and reporting features. - Lead by example: Write production-ready Python and PySpark code, perform code reviews, and optimize Spark configurations to improve performance and reduce costs. - Apply Agile methodologies such as Scrum to drive iterative development, foster team collaboration, and ensure continuous delivery of high-quality data solutions. - Support engineers through regular 1:1s, feedback, quarterly reviews, recognition, and performance management. Qualifications - Bachelor’s degree in Computer Engineering, Data Science, or equivalent practical experience. - 8+ years of experience in technology, specifically focused on data engineering, data warehousing, or big data architecture. - 2+ years of experience of leading a data engineering team. - Expertise in Python & PySpark: Deep experience writing and tuning distributed processing applications, handling data skew, and optimizing Spark memory management. - Advanced AWS Expertise: Proven track record of managing Amazon EMR for heavy-duty processing. - Experience with Big Data Infrastructure: Build the systems required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies (S3, EMR, Glue, Athena and Lambda). - Expert SQL skills for complex transformations, performance tuning, and deep-dive analytics. - Experience with Orchestration: Advanced proficiency with Airflow and Git. - AI-Driven Engineering: Proven track record of leveraging AI across the data engineering process to drive modernization, automate data quality checks, and enhance delivery outcomes. - Hands-on familiarity with AI-native tools such as Cursor, Claude, or GitHub Copilot to scale data development. Requirements - Performance Tuning Specialist: Ability to debug complex PySpark and/or Scala jobs and optimize EMR Instance Fleets/Spot Instances to balance performance with infrastructure costs. - Good to have experience with event-driven architecture and hands-on experience using AWS SQS for scalable, reliable event processing. - AWS certification is preferred, demonstrating expertise in designing and building scalable cloud-based data solutions. - Organized and collaborative—comfortable in a fast-moving, data-intensive environment. - Detail-oriented: Catches data quality issues early and implements automated course-corrections. - Strong communicator who aligns business needs with technical data constraints through clear trade-offs. - Deep problem solver who diagnoses pipeline bottlenecks and partners across teams to drive durable data solutions. Benefits - Parental leave- Maternity and Paternity - Flexible Time Offs (Earned Leaves, Sick Leaves, Birthday leave, Bereavement leave & Company Holidays) - In Office Daily Catered Breakfast, Lunch, Snacks and Beverages - Health cover for any hospitalization. Covers both nuclear family and parents - Tele-med for free doctor consultation, discounts on health checkups and medicines - Wellness/Gym Reimbursement - Pet Expense Reimbursement - Childcare Expenses and reimbursements - Employee referral program - Education reimbursement program - Skill development program - Cell phone reimbursement (Mobile Subsidy program). - Internet reimbursement/Postpaid cell phone bill/or both. - Birthday treat reimbursement - Employee Provident Fund Scheme offering different tax saving options such as Voluntary Provident Fund and employee and employer contribution up to 12% Basic - Creche reimbursement - Co-working space reimbursement - National Pension System employer match - Meal card for tax benefit - Special benefits on salary account

Product Engineer — Search You'll own the developer-facing search experience at Firecrawl — taking the retrieval and ranking improvements coming out of research and shipping them as a product developers can't stop using. This isn't a pure research role and it isn't a pure backend role. You sit at the intersection: you understand how the systems work deeply enough to improve them, and you care about how they feel to use obsessively enough to make them great. At a 26-person company, the gap between research and shipped product is exactly one person. You're that person. Salary Range: $180,000–$290,000/year (Range shown is for U.S.-based employees. Compensation outside the U.S. is adjusted fairly based on your country's cost of living. You can explore how we calculate this here: https://www.firecrawl.dev/careers/compensation.) Equity Range: Up to 0.15% Location: San Francisco, CA or Remote (Americas, UTC-3 to UTC-10) Job Type: Full-Time Experience: 3+ years in applied RL, ML engineering, or model training — with production systems Visa: US Citizenship/Visa required for SF; N/A for Remote About Firecrawl Firecrawl is the easiest way to extract data from the web. Developers use us to reliably convert URLs into LLM-ready markdown or structured data with a single API call. In just a year, we've hit 8 figures in ARR and 100k+ GitHub stars by building the fastest way for developers to get LLM-ready data. We're a small, fast-moving, technical team building essential infrastructure superintelligence will use to gather data on the web. We ship fast and deep. What You'll Do Ship search improvements that developers notice. Take retrieval and ranking improvements from research and turn them into product changes that make developers say "this just works." You know that a 200ms latency improvement isn't just a benchmark win — it's a better product. You ship the whole thing: the API change, the docs update, the example that makes it obvious. Own the search API end-to-end. You're responsible for how Firecrawl's search endpoint feels to integrate, use, and build on. That means response format, latency, error handling, pagination, filtering — every surface a developer touches. You're the person who notices when something is confusing before a user files a GitHub issue about it. Dogfood relentlessly. You build things with the API before you ship them. You feel the friction before your users do. You read every GitHub issue, every Discord thread, every support ticket that touches search — not because someone asked you to, but because that's where the product signal lives. Translate research into product decisions. You work closely with the Search/IR and RL Research Engineers. You understand their work well enough to make good product calls about what to prioritize, what to expose to users, and what to keep under the hood. You ask good questions. You push back when something technically elegant would make the API worse. Run fast product experiments. You form a hypothesis about what would make search better for developers, instrument it, ship it, measure it, and decide quickly. You're comfortable making calls with imperfect data because waiting for perfect data means shipping nothing. Raise the bar on developer experience. Firecrawl's users are technical. They have high standards. They notice when response formats are inconsistent, when error messages are unhelpful, when documentation doesn't match behavior. You notice too — and you fix it before they have to ask. What We're Looking For Obsessive about developer experience. You think about DX the way a designer thinks about pixels. Latency, response structure, error messages, API ergonomics — these things matter to you on a visceral level. You've built APIs that developers loved and you know the difference between an API that works and one that delights. Speaks both product and engineering fluently. You can read a ranking algorithm and understand its implications for the search experience. You can write the API spec and implement it yourself. You don't need a PM to tell you what matters or an ML engineer to explain why a retrieval change is significant. You connect those dots on your own. Hands-on builder who ships. You write code. You own features from design to deployment. You're comfortable with ambiguity and you don't need a perfectly scoped ticket to make progress. You ship something, learn from it, and iterate. Has a feel for search as a product. You've thought seriously about what makes search good — not just fast or accurate, but genuinely useful. You understand the difference between recall and precision and why developers care about both. You have intuitions about query understanding, result ranking, and when semantic search beats keyword search — and you've built products that put those intuitions to work. Brings production instincts. You've operated systems under real load. You know what breaks first, how to instrument what matters, and how to make good latency/quality tradeoffs. You're not just building features — you're building infrastructure developers depend on. Backgrounds that tend to do well: Engineers who've owned search or discovery features at developer-tools companies. Full-stack engineers with a strong backend bias who've shipped APIs used by thousands of developers. Engineers from search infrastructure teams who got frustrated by the distance between their work and the user experience. People who've built on top of Elasticsearch, Vespa, or vector databases — and cared enough about the product layer to go deeper than the query interface. What We're NOT Looking For Great engineers who don't care about DX. If you build technically excellent systems but think API ergonomics and documentation are someone else's problem, this isn't the role. The product experience is part of the job — not an afterthought. People who need a PM. There's no product manager between you and the work. You define what good looks like, you decide what to prioritize, and you own the outcome. If that's uncomfortable, you'll struggle here. Specialists who only work on one layer. If you're only interested in backend systems and tune out when the conversation shifts to how something is exposed to developers — or vice versa — this won't be a fit. This role requires you to hold both. Slow shippers. The research team will produce improvements faster than a slow product cycle can absorb them. We need someone who can take something from "this ranking model is better" to "this is live in the API with docs and an example" in days, not sprints. People who don't use the product. If you're not the kind of engineer who builds side projects with APIs like ours, reads the docs critically, and notices when something feels off — you'll miss the signal that makes this role work. A Note On Pace We operate at an absurd level of urgency because the window for what we're building won't stay open forever. If that excites you, keep reading. If it doesn't, no hard feelings — but this role probably isn't for you. Benefits & Perks Available to all employees - Salary that makes sense — $180,000–$290,000/year, based on impact, not tenure - Own a piece — Up to 0.15% equity in what you're helping build - Generous PTO — 15 days mandatory, anything after 24 days, just ask (holidays excluded); take the time you need to recharge - Parental leave — 12 weeks fully paid, for moms and dads - Wellness stipend — $100/month for the gym, therapy, massages, or whatever keeps you human - Learning & Development — Expense up to $1,000/year toward anything that helps you grow professionally - Team offsites — A change of scenery, minus the trust falls - Sabbatical — 3 paid months off after 4 years, do something fun and new Available to US-based full-time employees - Full coverage, no red tape — Medical, dental, and vision (100% for employees, 50% for spouse/kids) — no weird loopholes, just care that works - Life & Disability insurance — Employer-paid short-term disability, long-term disability, and life insurance — coverage for life's curveballs - Supplemental options — Optional accident, critical illness, hospital indemnity, and voluntary life insurance for extra peace of mind - Doctegrity telehealth — Talk to a doctor from your couch - 401(k) plan — Retirement might be a ways off, but future-you will thank you - Pre-tax benefits — Access to FSAs and commuter benefits (US-only) to help your wallet out a bit - Pet insurance — Because fur babies are family too Available to SF-based employees - SF HQ perks — Snacks, drinks, team lunches, intense ping pong, and peak startup energy - E-Bike transportation — A loaner electric bike to get you around the city, on us Interview Process Application Review — Send us your work and a quick note on why this excites you. Show us what you've shipped — search features, APIs, developer-facing products. A GitHub link, a product you've built, or a write-up of something you're proud of goes a long way. Intro Chat (~20 min) — A quick conversation to get to know each other before we go deep. We'll talk about what you've been working on, what drew you to Firecrawl, and what you're looking for in your next role. Time for your questions too. Technical Deep Dive (~60 min) — Go deep on search products and APIs you've built: architecture decisions, DX tradeoffs, how you've translated technical improvements into product changes. We'll explore a live problem — how you'd take a retrieval improvement and ship it as a better developer experience at Firecrawl. We're looking for product instincts, technical depth, and the ability to hold both at once. Founder Chat (~30 min) — Culture, pace, ownership, and how you like to work. Time for your questions too. Paid Work Trial (1–2 weeks) — Tackle a real search product problem with production implications. We evaluate on shipping speed, product judgment, and how well you balance technical quality with developer experience. Decision — We move fast after the trial. If you want to own the search experience at one of the fastest-growing developer infrastructure companies in AI — and you're the kind of engineer who won't stop until it's great — this is your shot. 👉 Apply now.

The salary for this role is £50,000. This role is being offered on a 12 Month Fixed Term Contract. Are you an experienced Azure Data Engineer with a passion for building scalable, high-quality data solutions? Can you design and optimise data pipelines using tools like Azure Databricks and Data Factory to deliver real business impact? Do you enjoy collaborating with cross-functional teams to turn complex data into valuable insights If so, we’d love to hear from you! At Livestock Information Ltd, our mission is to be an outstanding service provider of livestock data, empowering government, industry, and farmers to effectively manage disease and infection control, whilst enhancing productivity and innovation in agriculture. To achieve this, we need great people, who share in our values. As a Data Engineer at LI, you will play a key role in delivering scalable, high-quality data solutions that support critical business needs. In this role, you’ll design and build new data services, lead migrations of existing solutions, and ensure the ongoing performance and enhancement of live data platforms. Working in a collaborative, agile environment, you’ll partner with cross-functional teams including Product Owners, Business Analysts, Developers, and Testers to deliver impactful data products. You’ll work with a modern Azure data stack, including Databricks, Synapse, Data Factory, and Data Lake technologies, using tools like Azure DevOps to support end-to-end development and delivery. Responsibilities Your responsibilities will include - Designing & Implementing Data Storage Solutions on Azure: Select Azure data storage services appropriately and design data storage schemas, ensuring they are optimised for specific use cases. - Building and Maintaining Data Pipelines for Data Integration and Processing: Build and maintain data pipelines for data movement and process orchestration. Collect data from various sources, transform data into a practical format and load it into appropriate data storage solutions on Azure using tools such as Azure Data Factory and Azure Databricks. Ensure data pipelines are scalable and efficient. - Ensuring Data Quality & Accuracy Through Testing & Validation: Test and verify data at different phases of the data pipeline, from extraction through to loading. - Optimising Data Processing Performance Through Tuning & Monitoring: Ensure data processing is efficient and scalable by tuning the data pipeline and monitoring performance; identify and resolve bottlenecks in the data pipeline and optimise data processing algorithms. - Developing & Maintaining Data Models & Schemas: Develop and maintain data models and schemas optimised for specific use cases. Select the appropriate data modelling techniques and ensure the data schema is scalable and efficient. - Collaborating With Other Teams to Provide Data for Analytics & Reporting: Work closely with other teams to provide data they need to perform their job functions. - Ensuring Data Security & Privacy Prerequisites Are Followed: Ensure that data streamed and processed on Azure confirms with applicable data security and privacy requirements such as the General Data Protection Regulation (GDPR). - Working with Large Datasets & Performing Data Analysis: Work with large datasets of hundreds of millions and billions of rows of data and perform data analysis - Staying updated on the latest Azure features, updates and best practices to ensure they are adopted effectively as appropriate You may be required to undertake other duties assigned by your line manager as appropriate

The salary for this role is £50,000. This role is being offered on a 12 Month Fixed Term Contract. Are you an experienced Azure Data Engineer with a passion for building scalable, high-quality data solutions? Can you design and optimise data pipelines using tools like Azure Databricks and Data Factory to deliver real business impact? Do you enjoy collaborating with cross-functional teams to turn complex data into valuable insights If so, we’d love to hear from you! At Livestock Information Ltd, our mission is to be an outstanding service provider of livestock data, empowering government, industry, and farmers to effectively manage disease and infection control, whilst enhancing productivity and innovation in agriculture. To achieve this, we need great people, who share in our values. As a Data Engineer at LI, you will play a key role in delivering scalable, high-quality data solutions that support critical business needs. In this role, you’ll design and build new data services, lead migrations of existing solutions, and ensure the ongoing performance and enhancement of live data platforms. Working in a collaborative, agile environment, you’ll partner with cross-functional teams including Product Owners, Business Analysts, Developers, and Testers to deliver impactful data products. You’ll work with a modern Azure data stack, including Databricks, Synapse, Data Factory, and Data Lake technologies, using tools like Azure DevOps to support end-to-end development and delivery. Responsibilities Your responsibilities will include - Designing & Implementing Data Storage Solutions on Azure: Select Azure data storage services appropriately and design data storage schemas, ensuring they are optimised for specific use cases. - Building and Maintaining Data Pipelines for Data Integration and Processing: Build and maintain data pipelines for data movement and process orchestration. Collect data from various sources, transform data into a practical format and load it into appropriate data storage solutions on Azure using tools such as Azure Data Factory and Azure Databricks. Ensure data pipelines are scalable and efficient. - Ensuring Data Quality & Accuracy Through Testing & Validation: Test and verify data at different phases of the data pipeline, from extraction through to loading. - Optimising Data Processing Performance Through Tuning & Monitoring: Ensure data processing is efficient and scalable by tuning the data pipeline and monitoring performance; identify and resolve bottlenecks in the data pipeline and optimise data processing algorithms. - Developing & Maintaining Data Models & Schemas: Develop and maintain data models and schemas optimised for specific use cases. Select the appropriate data modelling techniques and ensure the data schema is scalable and efficient. - Collaborating With Other Teams to Provide Data for Analytics & Reporting: Work closely with other teams to provide data they need to perform their job functions. - Ensuring Data Security & Privacy Prerequisites Are Followed: Ensure that data streamed and processed on Azure confirms with applicable data security and privacy requirements such as the General Data Protection Regulation (GDPR). - Working with Large Datasets & Performing Data Analysis: Work with large datasets of hundreds of millions and billions of rows of data and perform data analysis - Staying updated on the latest Azure features, updates and best practices to ensure they are adopted effectively as appropriate You may be required to undertake other duties assigned by your line manager as appropriate