Role Description We are currently seeking an AI Data Engineer - Security (Kafka Experience) to join our team in Remote, Karnātaka (IN-KA), India. - Data Engineer (With Kafka experience) - Kafka: Strong expertise in Kafka (4-5 years), with hands-on experience designing and operating large-scale, highly available event-streaming platforms, including: - Partitioning strategies - Consumer group optimization - Schema management - Performance tuning - API-first data ingestion: Strong hands-on pulling data from REST/GraphQL APIs with auth (OAuth2, API keys), pagination, rate limits, retries/backoff, and webhooks; strong Python skills to normalize/enrich data and land it cleanly into S3 (schema, partitioning, Parquet). - AWS data lake, end to end: Comfortable building/operating S3-based lakes with layered zones (raw → harmonized → conformed → modeled), Glue Data Catalog, IAM/Secrets Manager, VPC endpoints, encryption, lifecycle/versioning, and cost/perf best practices (file sizing, compaction). - AWS Glue + PySpark expert: Designs and optimizes Glue jobs using PySpark/DynamicFrames, bookmarks for incremental loads, dependency packaging, robust error handling, logging/metrics, and unit tests; knows how to tune jobs for scale and cost. - Airflow orchestration: Writes clean, parameterized, idempotent DAGs (sensors, SLAs, retries, alerts), manages dependencies across pipelines, and uses Git-based CI/CD to promote changes safely. - Snowflake proficiency: Builds ELT models (staging/ODS/marts), tunes performance (warehouse sizing, clustering, micro-partitions, caching), uses Streams/Tasks/Snowpipe for CDC, and follows solid RBAC and data governance practices. Qualifications - 4-5 years of experience with Kafka - Strong Python skills - Experience with AWS services - Proficiency in Snowflake - Experience with Airflow Requirements - Hands-on experience with REST/GraphQL APIs - Experience in building S3-based data lakes - Expertise in AWS Glue and PySpark - Ability to write clean and parameterized DAGs in Airflow - Knowledge of ELT models and data governance practices Benefits - Flexible work arrangements - Access to a robust ecosystem of innovation centers - Opportunities for professional growth and development

Job Title: Data Engineer Position Type: Full-Time, Remote Working Hours: U.S. client business hours (with flexibility for pipeline monitoring and data refresh cycles) About the Role: Our client is seeking a Data Engineer to design, build, and maintain reliable data pipelines and infrastructure that deliver clean, accessible, and actionable data. This role requires strong software engineering fundamentals, experience with modern data stacks, and an eye for quality and scalability. The Data Engineer ensures data flows seamlessly from source systems to warehouses and BI tools, powering decision-making across the business. Responsibilities: Pipeline Development: - Build and maintain ETL/ELT pipelines using Python, SQL, or Scala. - Orchestrate workflows with Airflow, Prefect, Dagster, or Luigi. - Ingest structured and unstructured data from APIs, SaaS platforms, relational databases, and streaming sources. Data Warehousing: - Manage data warehouses (Snowflake, BigQuery, Redshift). - Design schemas (star/snowflake) optimized for analytics. - Implement partitioning, clustering, and query performance tuning. Data Quality & Governance: - Implement validation checks, anomaly detection, and logging for data integrity. - Enforce naming conventions, lineage tracking, and documentation (dbt, Great Expectations). - Maintain compliance with GDPR, HIPAA, or industry-specific regulations. Streaming & Real-Time Data: - Develop and monitor streaming pipelines with Kafka, Kinesis, or Pub/Sub. - Ensure low-latency ingestion for time-sensitive use cases. Collaboration: - Partner with analysts and data scientists to provide curated, reliable datasets. - Support BI teams in building dashboards (Tableau, Looker, Power BI). - Document data models and pipelines for knowledge transfer. Infrastructure & DevOps: - Containerize data services with Docker and orchestrate in Kubernetes. - Automate deployments via CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI). - Manage cloud infrastructure using Terraform or CloudFormation. What Makes You a Perfect Fit: - Passion for clean, reliable, and scalable data. - Strong problem-solving skills with debugging mindset. - Balance of software engineering rigor and data intuition. - Collaborative communicator who thrives in cross-functional environments. Required Experience & Skills (Minimum): - 3+ years in data engineering or back-end development. - Strong Python and SQL skills. - Experience with at least one major data warehouse (Snowflake, Redshift, BigQuery). - Familiarity with pipeline orchestration tools (Airflow, Prefect). Ideal Experience & Skills: - Experience with dbt for transformations and data modeling. - Streaming data experience (Kafka, Kinesis, Pub/Sub). - Cloud-native data platforms (AWS Glue, GCP Dataflow, Azure Data Factory). - Background in regulated industries (healthcare, finance) with strict compliance. What Does a Typical Day Look Like? A Data Engineer’s day revolves around keeping pipelines running, improving reliability, and enabling teams with high-quality data. You will: - Check pipeline health in Airflow/Prefect and resolve any failed jobs. - Ingest new data sources, writing connectors for APIs or SaaS platforms. - Optimize SQL queries and warehouse performance to reduce costs and latency. - Collaborate with analysts/data scientists to deliver clean datasets for dashboards and models. - Implement validation checks to prevent downstream reporting issues. - Document and monitor pipelines so they’re reproducible, scalable, and audit-ready. In essence: you ensure the business has accurate, timely, and trustworthy data powering every decision. Key Metrics for Success (KPIs): - Pipeline uptime ≥ 99%. - Data freshness within agreed SLAs (hourly, daily, weekly). - Zero critical data quality errors reaching BI/analytics. - Cost-optimized queries and warehouse performance. - Positive feedback from data consumers (analysts, scientists, leadership). Interview Process: - Initial Phone Screen - Video Interview with Pavago Recruiter - Technical Task (e.g., build a small ETL pipeline or optimize a SQL query) - Client Interview with Engineering/Data Team - Offer & Background Verification

• Design, build, and maintain high-quality dimensional data models and ELT pipelines that support marketing analytics across Paid Marketing, SEO, and Retailer Marketing, and attribution • Work closely with Data Scientists, Analysts, Data Engineers, and Marketing stakeholders to understand analytical needs, translate business questions into data requirements, and deliver trusted, decision-ready data assets • Lead efforts in data modeling, metric definition, testing, and documentation, owning data quality and resolving issues at their root cause across critical marketing workflows • Set standards and guide execution for marketing data pipelines, reviewing designs and implementations to ensure reliability, scalability, and analytical usability • Improve and evolve existing marketing data pipelines and workflows to reduce manual effort, improve performance, and increase the speed and confidence of analysis • Develop scalable analytics engineering patterns, including dimensional models, testing frameworks, and monitoring approaches, to support evolving marketing measurement needs.

What You'll Do About the Role The Senior Manager of Financial Insights is a role within Avalara's Global Analytics and Insights organization. You will deliver accurate, data-driven financial insights that inform strategic decision-making across the company. Partnering with the CFO, Finance, and department leaders, you will analyze our performance, model financial impacts, and develop defensible forecasts that guide operational and investment decisions. You will serve as the organization's financial insights expert — connecting business drivers to financial outcomes, interpreting the implications of strategic choices, and enabling a deeper understanding of how decisions translate to revenue, margin, and profitability. You will report to the Sr Director of Value Creation Insights. This position is remote in the United States. (#LI-Remote) What Your Responsibilities Will Be Responsibilities Financial Analysis & Forecasting - Manage accurate, transparent financial models and forecasts that inform short- and long-term business planning. - Evaluate the financial impact of strategic and operational decisions, providing applicable insights to the CFO and business leaders. - Conduct scenario analysis and sensitivity modeling to assess potential risks and outcomes. - Translate projects into costs and track results against projections. - Be a trusted advisor for financial performance management and forecasting processes. Strategic Decision Support - Partner with leaders including General Managers (GM's), Accounting, Financial Planning and Analysis, Sales, Marketing, Product, and Operations to assess costs of business strategies. - Deliver clear, data-backed recommendations that align with Avalara's growth and profitability goals. - Support strategic planning, investment evaluations, and cost optimization plans with detailed financial insights. - Communicate complex financial concepts and trends in a clear, narrative-driven format tailored for executive audiences. Performance Measurement and Reporting - Maintain standard reporting and KPI frameworks to measure important financial and operational performance metrics. - Provide regular performance updates and variance analyses to senior leadership with proposed actions to mitigate risk moving forward. - Improve financial data accuracy, reporting processes, and business intelligence assets. - Create scalable reporting mechanisms that improve transparency and reduce dependency on ad hoc analyses. Operational Partnership & Enablement - Collaborate with business and finance partners to define financial success metrics and performance drivers. - Identify trends and opportunities to improve forecasting accuracy and business efficiency. - Ensure data integrity across systems, leading structured validation and transformation projects. - Mentor analysts and peers on financial modeling, data interpretation, and insight generation best practices. What You'll Need to be Successful What You Need to Succeed - 8+ years of experience in financial planning and analysis, business insights, or strategic finance roles (or 5+ years with a Master's). - Demonstrated expertise in financial modeling, forecasting, and performance measurement. - Proficiency with BI and analytical tools such as Power BI, Tableau, or similar platforms. - Advanced SQL skills with experience in financial data modeling and validation. - Connect analytics to operational and strategic outcomes. - Experience improving financial visibility and ensuring data-driven decision-making. - Experience in a SaaS, B2B, or technology-driven organization. - Prior exposure to working with or supporting a CFO or Finance leadership team. - Familiarity with revenue forecasting, cost modeling, and business case development. - Experience leading or partnering with FP&A or strategic finance teams. Pay Range Details The base pay range(s) below are provided in compliance with state specific laws. Pay ranges may be different in other locations. Colorado $136,400-$225,000 (annually) Washington $136,400-$248,600 (annually) California $136,400-$272,500(annually) NYC $165,100-$272,500 (annually) The pay range above is the general base pay range for a successful candidate in the state listed. The successful candidate’s actual salary/wage may be based on various factors, such as geographic location, candidate experience and qualifications, as well as market and business considerations. This role is eligible for an annual bonus based on individual and company performance, depending on the terms of the applicable plan and the employee’s role. Avalara is an AI-first Company AI is embedded in our workflows, decision-making, and products. Success here requires embracing AI as an essential capability. - You’ll bring experience using AI and AI-related technologies, ready to thrive here. - You’ll apply AI every day to business challenges - improving efficiency, contributing solutions, and driving results for your team, our company, and our customers. - You’ll grow with AI by staying curious about new trends and best practices, and by sharing what you learn so others can benefit too. How We'll Take Care of You Total Rewards In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses. Health & Wellness Benefits vary by location but generally include private medical, life, and disability insurance. Inclusive culture and diversity Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. We also have a total of 8 employee-run resource groups, each with senior leadership and exec sponsorship. What You Need To Know About Avalara We’re defining the relationship between tax and tech. We’ve already built an industry-leading cloud compliance platform, processing over 54 billion customer API calls and over 6.6 million tax returns a year. Our growth is real - we're a billion dollar business - and we’re not slowing down until we’ve achieved our mission - to be part of every transaction in the world. We’re bright, innovative, and disruptive, like the orange we love to wear. It captures our quirky spirit and optimistic mindset. It shows off the culture we’ve designed, that empowers our people to win. We’ve been different from day one. Join us, and your career will be too. We’re An Equal Opportunity Employer Supporting diversity and inclusion is a cornerstone of our company — we don’t want people to fit into our culture, but to enrich it. All qualified candidates will receive consideration for employment without regard to race, color, creed, religion, age, gender, national orientation, disability, sexual orientation, US Veteran status, or any other factor protected by law. If you require any reasonable adjustments during the recruitment process, please let us know.