Data Engineer

Data Engineer

Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.

Must have skills: PySpark

Minimum 5 year(s) of experience is required. 15 years full time education is required.

Roles & Responsibilities:

• Develop and maintain ETL pipelines using PySpark for data ingestion, transformation, and aggregation.
• Write optimized and reusable PySpark code to process large-scale datasets.
• Work with structured and unstructured data sources (CSV, JSON, Parquet, Avro, relational DBs, etc.).
• Optimize Spark jobs for scalability, reliability, and performance.
• Collaborate with data engineers, analysts, and business stakeholders to deliver clean and reliable datasets.
• Implement data quality checks, monitoring, and logging for pipelines.
• Work with cloud storage and big data frameworks (HDFS, Hive, Delta Lake, S3, ADLS, BigQuery).
• Apply best practices for code versioning (Git), testing, and CI/CD deployment.
• Document design, workflows, and technical solutions.

Professional & Technical Skills:

• Proficiency in PySpark, Git, Testing, CI/CD deployment.
• Work with cloud storage and big data frameworks (HDFS, Hive, Delta Lake, S3, ADLS, BigQuery).
• Strong understanding of data modeling and database design principles.
• Experience with data warehousing solutions and architecture.
• Familiarity with cloud platforms such as AWS or Azure.
• Knowledge of data governance and data quality frameworks.

The candidate should have minimum 7 years of experience in PySpark. This position is based at our Bengaluru office.

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