Data Engineer

Data Engineer
Role Summary
We are looking for a  Data Engineer with 1–3 years of experience  to design, build, and maintain data pipelines that support analytics and business reporting. The ideal candidate will have hands-on experience with data processing, SQL, and cloud-based data platforms and be eager to grow in large-scale data engineering and analytics systems.

Key Responsibilities
Build and maintain  ETL / ELT data pipelines  from multiple data sources.
Develop and optimize  SQL queries  for data transformation and reporting.
Work with structured and semi-structured data (CSV, JSON, Parquet).
Assist in designing  data models  for analytics and reporting use cases.
Perform data validation, quality checks, and troubleshooting.
Collaborate with data analysts, BI developers, and backend teams.
Support batch and basic real-time data processing workflows.
Document data pipelines and follow data engineering best practices.
Required Skills
1–3 years of hands-on experience in  Data Engineering or related roles .
Strong knowledge of  SQL  (joins, subqueries, window functions).

Experience with  ETL / ELT concepts  and data pipelines.
Programming experience in  Python  (preferred) or Java/Scala (basic).
Exposure to  cloud platforms  (AWS / Azure / GCP).

Experience with data warehouses or big-data platforms such as:
Snowflake, Redshift, Big Query, Azure Synapse, Databricks (any one).
Good to Have

Experience with  Apache Spark / PySpark .
Exposure to orchestration tools (Airflow, Azure Data Factory).
Understanding of  data warehousing concepts  (fact & dimension tables).

Experience with version control tools (Git).
Familiarity with basic Dev Ops practices and CI/CD.