Data Engineer — Analytics & Migration

Hi All,

Role Summary

We’re looking for a hands-on Data Engineer to own the data layer of customer go-lives — ensuring migrations are validated, analytics pipelines are hardened, and business dashboards are powered by accurate, performant data. You’ll be responsible for validating and signing off on end-to-end data migrations, building high-quality SQL models, and implementing automated data quality checks to catch issues early. This is a highly technical and impact-driven role focused on migration testing, SQL performance tuning, and data quality automation — aligning with AWS and industry best practices.

Key Responsibilities

• End-to-End Migration Validation: Design and execute functional and performance validation for data migrations — including parity, nullability, PK/FK, duplication, and sampling checks — with complete documentation and sign-off aligned to AWS migration testing guidelines.
• Advanced SQL Development: Write and optimize analytical SQL (CTEs, window functions, incremental loads). Use EXPLAIN plans to tune query performance and ensure indexes and statistics support BI workloads.
• Automated Data Quality Frameworks: Implement and maintain data validation frameworks using Great Expectations, Deequ, or similar tools. Automate validation and publish Data Docs to ensure transparency across teams.
• Modeling & Documentation (dbt): If using dbt, build models with tests, exposures, and documentation to ensure traceability between dashboards and upstream data sources.
• Orchestration & Reliability: Productionize data validation and transformation jobs within Airflow DAGs, ensuring welldefined SLAs, alerts, and reliable pipeline operations.

(Optional) Cloud Data Engineering: Build incremental pipelines and optimize batch processing for Snowflake (Streams & Tasks) or PostgreSQL, ensuring performance and cost efficiency.

Minimum Qualifications

Experience: 4–7+ years as a Data Engineer or Analytics Engineer.

SQL Expertise: Advanced proficiency in SQL and strong RDBMS fundamentals (PostgreSQL required), with proven experience in query tuning using EXPLAIN/analyze.

Migration Validation: Hands-on experience designing and executing data migration validation (parity, integrity, and performance testing).

• Tooling Knowledge: Experience with one or more of the following — dbt, Great Expectations or Deequ/PyDeequ, Airflow.

Version Control: Comfortable with Git-based workflows and CI/CD integration.

Nice to Have

• Experience with Snowflake (Streams, Tasks, cost optimization, and warehouse tuning).
• Exposure to BI tools such as Looker, Power BI, Tableau, or Metabase.
• Working knowledge of Python for lightweight data transformations and validation frameworks.

Location:- work from home

Job Type: Full-time

Benefits:

• Work from home