Responsibilities:

· Design, develop, and maintain data pipelines to ingest, transform, and serve data from multiple sources.

· Support batch and near-real-time data processing, ensuring data accuracy, freshness, and reliability.

· Assist in managing and optimizing data lakes, lakehouses, and data warehouses.

· Develop and optimize SQL and Python-based transformations for reporting and analytics.

· Implement basic data quality checks, logging, and monitoring.

· Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements.

· Participate in code reviews, testing, documentation, and CI/CD processes.

· Continuously learn and adopt modern data engineering and AI-enabled data practices.

Key Technical Skills & Responsibilities

· Strong working knowledge of Python and SQL for data processing.

· Experience building ETL/ELT pipelines using industry-standard practices.

· Familiarity with cloud data platforms such as:

ü Snowflake

ü Microsoft Fabric (OneLake, Lakehouse, Data Pipelines)

ü AWS(Redshift, Glue) / Azure Data Lake / Google BigQuery

· Understanding of data modeling concepts (fact/dimension tables, star schema).

· Experience or exposure to orchestration and transformation tools such as Airflow, DBT, Spark, or Dask.

· Working knowledge of Git and CI/CD pipelines.

· Exposure to BI and visualization tools such as Power BI or Apache Superset.

· Basic understanding of cloud security, access control, and cost optimization.

Eligibility Criteria:

· Bachelor’s degree in computer science, Engineering, or a related discipline.

· 3+years of hands-on experience in data engineering or a closely related role.

· Experience supporting or maintaining production data pipelines.

· Strong problem-solving skills and eagerness to learn new technologies.

· Good written and verbal communication skills.

· Ability to work effectively in a collaborative team environment.

DATA ENGINEER