Data Engineer

Title: Data Engineer - PySpark

About CentricaSoft:

CentricaSoft 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 PySpark Developer who thrives in a fast-paced, collaborative environment.

Role Summary

We are looking for a PySpark 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 PySpark-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 PySpark 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/SageMaker, EMR/Redshift; Azure Data Factory/Databricks; GCP BigQuery/Dataflow/Dataproc, AirFlow, 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