Job Description Data Engineer :

Location : Noida / Gurgaon

Experience : 4 to 5 Years

We are looking for an experienced Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms on AWS.

The role requires strong expertise in Python, SQL, ETL/ELT pipelines, Airflow, and AWS data services to enable reliable, secure, and high-performance data solutions for analytics and business reporting. Candidates with exposure to the BFSI / lending / banking domain will be preferred.

Key Responsibilities :

- Design, build, and maintain scalable ETL/ELT pipelines and data workflows on AWS.

- Develop and optimize data models (OLTP/OLAP), schemas, and warehousing solutions (e.g., Redshift, Snowflake, or similar).

- Build data ingestion frameworks for batch and streaming data from diverse sources (APIs, RDBMS, files, event streams).

- Implement data quality checks, validation rules, and monitoring for data reliability and SLAs.

- Write efficient, production-grade Python and SQL for data transformations and orchestration.

- Manage and optimize data storage, partitioning, and performance (query tuning, indexing, cost optimization).

- Implement orchestration and workflow management (e.g., Airflow/Step Functions).

- Collaborate with stakeholders to translate business requirements into technical specs and data contracts.

- Ensure data security, governance, lineage, and compliance (IAM, encryption, PII handling).

- Set up observability for pipelines (logging, metrics, alerting) and support on-call rotations.

- Contribute to CI/CD for data workloads, infrastructure-as-code, and best practices documentation.

Required Skills :

- 4 to 5 years of hands-on experience in Data Engineering.

- Strong experience with AWS services such as S3, Glue, Athena, Lambda, Redshift, Step Functions, EMR/Glue Spark, IAM, and CloudWatch.

- Proficiency in Python and advanced SQL.

- Experience with ETL/ELT pipelines, data modeling, and data warehousing.

- Hands-on experience with Airflow or equivalent orchestration tools.

- Good understanding of data quality, monitoring, and performance tuning.

- Familiarity with Git, CI/CD, and Infrastructure as Code (Terraform / CloudFormation).

Preferred :

- Exposure to BFSI / Banking / NBFC / Lending domain.

- Experience with Kinesis / Kafka / MSK.

- Knowledge of Docker, ECS / EKS.

- Familiarity with Parquet, Delta, Iceberg, and Lake Formation.