Vacancy description
Neemtree
Bombay, भारत
About the Role : We're seeking a Data Engineer with 3 - 4 years of experience to join our growing tech team. The ideal candidate will have hands-on experience in building and managing scalable data systems on AWS using Spark and modern data https://jobeax.com/link/OfTNakiwtq51n9YB Responsibilities : - Design, build, and maintain end-to-end data pipelines for ingestion, transformation, and delivery of high-volume data.- Develop Spark-based ETL/ELT workflows for both batch and real-time streaming data.- Integrate data from multiple internal and external systems using Kafka, Kinesis, or other streaming frameworks.- Build and manage data models, warehouses, and lakehouses using AWS services such as S3, Glue, Redshift, Athena, etc.- Implement data quality checks, validation rules, and monitoring to ensure reliability and consistency.- Collaborate with data analysts and scientists to provide clean, structured datasets optimized for analytics and ML.- Work with orchestration tools (Airflow, MWAA, Step Functions, etc.) for automated workflow scheduling.- Continuously optimize data pipelines for cost, scalability, and https://jobeax.com/link/iVTIKAC0ziCuS1Ni Stack : - Spark, AWS (S3, Glue, Redshift, Kinesis), Kafka, Airflow, Python, https://jobeax.com/link/wngoC12EjrRb3nCt Skills : - Strong programming skills in Python for data manipulation and automation.- Hands-on expertise in Apache Spark (PySpark or Spark SQL) for large-scale data processing.- Deep understanding of AWS data ecosystem - S3, Glue, Lambda, Redshift, Athena, EMR, Kinesis, IAM.- Experience with real-time streaming platforms such as Kafka, Kinesis, or Flink.- Strong command of SQL and data modeling (star schema, dimensional modeling, partitioning).- Proficiency with data orchestration and workflow management tools (Airflow, Step Functions, etc.).- Familiarity with Git, CI/CD, and modern development best practices.- Experience working in Linux/Unix environments and handling large datasets https://jobeax.com/link/PxycnitIfDZGOH0O to Have : - Exposure to data lakehouse technologies (Delta Lake, Iceberg, Hudi).- Understanding of data governance, cataloging, and lineage tools (Glue Data Catalog, Amundsen, DataHub).- Familiarity with containerization and deployment (Docker, ECS, EKS).- Basic understanding of AI/ML.Qualifications : - Bachelor's degree in Computer Science, IT, Engineering, or related technical field.- 3 - 4 years of experience in data engineering, big data, or analytics infrastructure. (ref:hirist.tech)