Chainalysis’ Enterprise Data & Analytics team is responsible for generating insights from Chainalysis’ corporate functions and GTM functions. We do this by ingesting, storing and enabling consumption of trusted Account Journey data, metrics and insights across the B2B Enterprise Funnel. We design and implement the critical infrastructure that unifies data across business systems, empowering analytics, operational excellence, and advanced AI initiatives. Our mission is to deliver secure, scalable, and reliable data solutions that enable every part of Chainalysis to thrive in an ever-evolving technology landscape. As a Senior Data Engineer, Enterprise Data Analytics - you work across low-code platforms and custom cloud-native services, leveraging your software engineering background and DevOps experience. This role requires strong problem solving skills, and the ability to partner with key stakeholders and drive strategic collaboration to shape the future of our enterprise data platform. You'll work across low-code platforms and custom cloud-native services. In this role, you’ll: - Design and implement robust, scalable integrations between Databricks and key enterprise business systems (Netsuite, Workday, SalesForce) - Translate business requirements into technical specifications and integration workflows - Develop, and maintain automated data pipelines using a combination of low-code tools and custom AWS solutions (Lambda, Step Functions, S3, CloudWatch, VPCs, IAM) - Own the provisioning and management of infrastructure for integrations by applying Infrastructure as Code principles with Terraform - Mentor engineers and champion best practices in software engineering, source control (Gitflow), and DevOps workflows within Github repositories - Collaborate closely with data scientists, product managers, and stakeholders to ensure integrations deliver transformative business value - Proactively monitor, troubleshoot, and ensure reliability and observability of integration solutions across distributed systems We’re looking for candidates who have: - Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience - Minimum 6+ years of hands-on experience in software engineering - Hands-on expertise with Terraform and modern DevOps practices, including CI/CD and infrastructure lifecycle automation - Proficiency in Python or Node.js - AWS experience: Lambda, Step Functions, S3, CloudWatch, VPCs, IAM. - Hands-on experience with Databricks, Snowflake or similar for data warehousing, modeling, or pipeline optimization. - Experience with modern source control workflows (Gitflow), using Github You might also have: - Hands-on experience with Databricks or Snowflake, especially in data warehousing, modeling, or pipeline optimization. About Chainalysis Blockchain technology is powering a growing wave of innovation. Businesses and governments around the world are using blockchains to make banking more efficient, connect with their customers, and investigate criminal cases. As adoption of blockchain technology grows, more and more organizations seek access to all this ecosystem has to offer. That’s where Chainalysis comes in. We provide complete knowledge of what’s happening on blockchains through our data, services, and solutions. With Chainalysis, organizations can navigate blockchains safely and with confidence. You belong here. At Chainalysis, we believe that diversity of experience and thought makes us stronger. With both customers and employees around the world, we are committed to ensuring our team reflects the unique communities around us. We’re ensuring we keep learning by committing to continually revisit and reevaluate our diversity culture. We encourage applicants across any race, ethnicity, gender/gender expression, age, spirituality, ability, experience and more. If you need any accommodations to make our interview process more accessible to you due to a disability, don't hesitate to let us know. You can learn more here. We can’t wait to meet you.

About Cylinder Founded in 2021 and offered as an employer benefit, Cylinder (formerly Vivante Health) delivers personalized, clinician-backed care to those suffering from digestive health issues through its virtual health platform. Cylinder’s tech-forward, human-first program connects members to the right level of support at the right time through an easy interface, bringing the healthcare ecosystem together to align around member needs. Cylinder’s dedicated care teams help members proactively address their gut health from every angle – decreasing costs, reducing absenteeism, and improving their quality of life, at scale. Cylinder’s vision is to create a world where people receive convenient, personalized, and affordable access to the quality digestive healthcare they need to improve their overall health. Position Summary We’re seeking a highly experienced Senior Data Engineer to lead our data infrastructure initiatives and mentor our growing engineering team. As a Senior Data Engineer, you will architect and optimize enterprise-scale data solutions while driving technical strategy across the organization. You'll play a pivotal role in establishing data engineering best practices and building systems that can scale with our rapidly growing member base. Why is this a great opportunity for a data engineer? You'll be joining at a pivotal moment where your technical leadership will directly shape our data strategy. The problem domain offers unique challenges - integrating previously disconnected healthcare data sources, building sophisticated GI patient models, and discovering insights that tangibly improve patient outcomes. As a senior contributor, you'll have significant autonomy in technical decisions and the opportunity to build a world-class data engineering function from the ground up. Key Leadership Responsibilities: - Architect and design scalable, fault-tolerant data pipelines for complex healthcare data ingestion, transformation, and reporting - Lead technical decision-making for data infrastructure and tooling selection - Mentor junior engineers and establish engineering best practices across the team - Drive cross-functional collaboration with Data Science, Business Intelligence, and Product teams - Champion data quality initiatives and establish robust monitoring and alerting systems - Design and implement solutions for complex distributed system challenges - Evaluate and implement emerging technologies to maintain our competitive edge Responsibilities Include: - Design and implement enterprise-grade data architectures with emphasis on scalability, reliability, and maintainability - Lead code reviews and establish coding standards that promote excellence across the engineering organization - Drive strategic partnerships with product stakeholders, translating complex business requirements into elegant technical solutions - Own end-to-end delivery of critical data infrastructure projects - Establish comprehensive testing strategies, documentation standards, and operational procedures - Continuously evaluate and optimize system performance, cost efficiency, and reliability - Serve as subject matter expert for healthcare data compliance and security requirements You'll be a good fit here if you bring: - Technical Leadership: You have a proven track record of architecting complex data systems and leading technical initiatives in fast-paced environments. - Healthcare Impact: You're passionate about leveraging data to improve patient outcomes and understand the unique challenges of healthcare data. - Security Excellence: You have deep expertise in healthcare data security, HIPAA compliance, and implementing robust data governance frameworks. - Collaboration & Mentorship: You excel at leading cross-functional teams and developing junior talent. - Innovation Mindset: You stay current with emerging technologies and can evaluate their strategic fit for our organization. Desired Qualifications - Bachelor's degree in Computer Science, Engineering, or related field, or equivalent professional experience - 5+ years of demonstrated experience architecting and building production data pipelines and MLOps environments - Expert-level proficiency in SQL and Python with demonstrated experience in performance optimization - Deep expertise with modern data stack technologies including dbt, Airflow, BigQuery, and cloud-native solutions - Extensive experience with major cloud platforms (AWS, GCP, or Azure) including infrastructure-as-code practices - Proven track record working with healthcare, medical, or population health data - Outstanding communication and leadership skills with experience mentoring engineering teams - Experience establishing data governance and compliance frameworks in regulated industries Preferred Qualifications - Advanced degree in Computer Science, Data Engineering, or related field - Extensive experience with Google Cloud Platform, including BigQuery, Vertex AI, IAM, Pub/Sub, Dataflow, and Cloud Composer - Expert-level experience with Terraform and infrastructure automation - Experience with real-time streaming data architectures - Track record of successfully scaling data systems in high-growth startup environments - Published thought leadership or contributions to open-source data engineering projects Cylinder is an equal opportunity employer. We believe that creating safe spaces where everyone can be their authentic selves is key to a successful team. We welcome and embrace all identities, cultures, and backgrounds.

• Build and maintain observability frameworks to monitor the health, performance, and reliability of data and analytic platforms • Implement tools for real-time monitoring, logging, and alerting to ensure proactive issue detection and resolution • Analyze system metrics and logs to identify trends, anomalies, and areas for improvement • Design and implement intelligent automation solutions to streamline data and analytic processing workflows and platform operations • Develop scripts, tools, and frameworks to automate repetitive tasks and improve system efficiency • Collaborate with cross-functional teams to identify automation opportunities and implement solutions • Ensure high availability and fault tolerance of the platform through robust monitoring and automation strategies

At DICK’S Sporting Goods, we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve. If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today! OVERVIEW: On the Athlete Data team, we build the data foundation that powers personalized customer experiences, loyalty programs, and marketing insights. Our work spans multiple systems and partners, and—just like all great teams—it requires trust, clarity, discipline, and collaboration. We’re looking for a Senior Data Engineer who values thoughtful problem‑solving, clean design, and strong data hygiene. Someone who can move between conceptual modeling and hands‑on implementation, and who enjoys working in an environment where everyone succeeds through the strengths they bring to the team. Capable engineers thrive here because we emphasize transparency, respect, steady improvement, and shared wins. Job Purpose: As a Senior Data Engineer on the Athlete team, you’ll work across a diverse and evolving data ecosystem that supports critical marketing functions. The role requires the ability to operate both deep within complex data domains and broadly across many systems, partners, and vendors. You’ll turn loosely defined business problems into clear, executable data solutions, helping bring structure and momentum to ambiguous work. You’ll play a key role in designing, building, and evolving data pipelines and models—especially in environments that involve sensitive customer data, identity resolution, and the unification of disparate sources. Success in this role depends on strong technical fundamentals, sound data judgment, and the ability to collaborate effectively across analytics, engineering, marketing, and product teams. Responsibilities: Build High‑Quality Pipelines - Develop reliable data pipelines using SQL, Python, Databricks/Spark. - Improve and modernize existing pipelines for clarity, performance, and maintainability. - Add tests, documentation, lineage, and observability to strengthen trust. Model Data Across Many Systems - Translate complex, multi‑source schemas into clear conceptual and physical models. - Handle grain alignment, key logic, and definition clarity with care. - Design models that scale and reduce friction for analysts, product, and downstream users. Protect Customer Data - Apply disciplined data hygiene and privacy-first patterns. - Safely move and store sensitive customer data in compliance with organizational standards. Collaborate Across the Field - Partner with analysts, product managers, marketing teams, data scientists, vendor teams, and other engineers. - Communicate assumptions, trade‑offs, and decision points clearly. - Bring clarity to ambiguous problems and help guide the team toward the best path forward. Lift the Team Like any high-performing team, we win together: - Share knowledge, document meaningfully, and help strengthen team patterns. - Support teammates through code reviews, pairing, and problem‑solving. - Use AI‑assisted tools to accelerate documentation, test generation, and iteration. What Helps You Succeed Here - Strong SQL and Python fundamentals - Experience with Databricks/Spark or similar large‑scale platforms - Clarity in thinking about data models and transformations - Detail‑orientated and disciplined data hygiene - Experience in refactoring codebase, cataloging/data governance, and agile development are a plus - Ability to break down complex problems and communicate them clearly - Curiosity and willingness to learn new tools/contexts quickly - Team-first mindset — you share, collaborate, and elevate others QUALIFICATIONS: - Bachelor's Degree or equivalent level preferred - General Experience: Experience enables job holder to deal with the majority of situations and to advise others (Over 3 years to 6 years) - Managerial Experience: Basic experience of coordinating the work of others (4 to 6 months) #LI-FD1 VIRTUAL REQUIREMENTS: At DICK’S, we thrive on innovation and authenticity. That said, to protect the integrity and security of our hiring process, we ask that candidates do not use AI tools (like ChatGPT or others) during interviews or assessments. To ensure a smooth and secure experience, please note the following: - Cameras must be on during all virtual interviews. - AI tools are not permitted to be used by the candidate during any part of the interview process. - Offers are contingent upon a satisfactory background check which may include ID verification. If you have any questions or need accommodations, we’re here to help. Thanks for helping us keep the process fair and secure for everyone! Targeted Pay Range: $83,000.00 - $138,200.00. This is part of a competitive total rewards package that could include other components such as: incentive, equity and benefits. Individual pay is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all teammate pay regularly to ensure competitive and equitable pay.DICK'S Sporting Goods complies with all state paid leave requirements. We also offer a generous suite of benefits. To learn more, visit www.benefityourliferesources.com.