DATA ENGINEER

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.