Senior engineer, data engineering

4 weeks ago

North, India CentricaSoft Full time

Title: Data Engineer - Py Spark About Centrica Soft: Centrica Soft is a data-driven technology partner delivering end-to-end data solutions for our clients. We design, build, and scale modern data platforms that empower business decisions. We're growing our data engineering team and seeking a hands-on Py Spark Developer who thrives in a fast-paced, collaborative environment. Role Summary We are looking for a Py Spark Developer with solid AWS or Azure or GCP experience and in-depth knowledge of CI/CD pipelines with Parquet/JSON/Avro/Iceberg/Databricks. The candidate will work on multiple ETL data processing integrations, including API data pulls, Database extracts, and handling semi-structured data. Strong SQL skills and excellent communication are essential. Atleast 1 Cloud certification from AWS (preferable) or Azure or GCP in Data Engineer area, Key Responsibilities Develop, optimize, and maintain Py Spark-based data processing pipelines for large-scale data workloads. Design and implement ETL/ELT processes, including API data ingestion, database extracts, and ingestion of semi-structured data (JSON, Parquet, Avro, etc.). Build and maintain CI/CD pipelines for data engineering workloads (code, tests, deployments, and monitoring) with data quality checks, logging, and error handling to ensure robust data pipelines. Optimize SQL queries and data models for performance and scalability. Contribute to documentation, best practices, and knowledge sharing within the team. Qualifications ~2-5 years of hands-on experience in data engineering. ~ Proficiency in Py Spark and Spark-based data processing with Parquet/JSON/Avro/Iceberg/Databricks. ~ Solid cloud experience (AWS or Azure or GCP) with data services (e.g., AWS Glue/Sage Maker, EMR/Redshift; Azure Data Factory/Databricks; GCP Big Query/Dataflow/Dataproc, Air Flow, etc). ~ Strong understanding of CI/CD concepts and experience implementing pipelines (e.g., Git, CI servers, containerization, automated testing, deployment automation). ~ Deep SQL expertise (query tuning, performance optimization, complex joins, window functions). ~ Excellent communication skills and ability to collaborate with cross-functional teams. ~ Familiarity with big data processing frameworks, data modeling, and data governance concepts. Certifications: Atleast 1 Cloud certifications from AWS or Azure in Data Engineer area , Nice-to-have Experience with streaming data (Kafka/Kinesis), and real-time processing. Knowledge of data visualization or BI tools (Power BI, Tableau) is a plus. What We Offer Hybrid work culture with a mix of on-site and remote work Competitive salary and comprehensive benefits Flexible work arrangements and a supportive, collaborative team Opportunities to work on impactful, scalable data platforms Professional development support and certification encouragement

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