Senior Data Engineer:

We are looking for a hands-on Data Engineer who will play a key role in ensuring the accuracy, reliability, and performance of data during customer go-lives.

This role focuses on validating data migrations, building optimized SQL-based data models, and implementing automated data quality checks using Python to support business analytics and reporting.

Key Responsibilities:

Data Migration Validation:

- Validate end-to-end data migrations to ensure accuracy and completeness.

- Perform checks such as data parity, nullability, duplicates, and referential integrity.

- Document validation results and support migration sign-off.

SQL Development & Optimization:

- Write and optimize complex SQL queries (CTEs, joins, window functions).

- Analyze query performance using EXPLAIN plans and improve efficiency.

- Build scalable data models to support analytics use cases.

Data Quality & Automation (Python-Driven):

- Develop automated data validation checks using Python.

- Work with data quality frameworks like Great Expectations, Deequ, or similar tools.

- Build reusable validation scripts and ensure data reliability.

Data Modeling & Documentation:

- Build and maintain data models using dbt (if applicable).

- Implement tests, documentation, and lineage tracking.

Workflow Orchestration:

- Schedule and manage pipelines using Airflow.

- Monitor workflows, handle failures, and ensure SLA adherence.

(Optional) Cloud & Warehousing:

- Work with PostgreSQL, Snowflake, or similar data warehouses.

- Optimize batch processing and data pipelines for performance.

Required Skills & Experience:

- 4 - 10 years of experience in Data Engineering / Analytics Engineering.

- Strong expertise in SQL and Python (both are mandatory).

- Hands-on experience with PostgreSQL or similar relational databases.

- Experience in data migration validation / data quality checks.

- Strong understanding of query optimization and performance tuning.

- Experience with at least one of the following: dbt, Airflow, Great Expectations, or Deequ.

- Familiarity with Git and version control workflows.

Nice to Have:

- Experience with Snowflake or cloud platforms (AWS preferred).

- Exposure to BI tools (Power BI, Tableau, Looker, Metabase).

- Experience building scalable data pipelines.

Why Join Us:

- Work on high-impact, data-critical projects.

- Opportunity to build robust and scalable data systems.

- Collaborative and fast-paced environment.