<p><p><b>Description :</b></p><br/><p><b>Job Summary :</b></p><br/><p>We are seeking a highly skilled Data Engineer to design, build, and optimize scalable data pipelines using Snowflake, AWS services, and Apache Spark.
You will be responsible for real-time and batch data ingestion, transformation, and orchestration across cloud platforms.</p><br/><p>Notice Period - 0 to 15 days.</p><br/><p><b>Key Responsibilities :</b></p><br/><p>- Develop and maintain data pipelines using AWS Glue, Lambda, EMR, and Snowflake.</p><br/><p>- Implement real-time ingestion using Snowpipe and Streams for CDC (Change Data Capture).</p><br/><p>- Write efficient PySpark or Scala Spark jobs for large-scale data processing.</p><br/><p>- Automate workflows and orchestrate jobs using AWS Step Functions, Airflow, or similar tools.</p><br/><p>- Optimize Snowflake queries and warehouse performance.</p><br/><p>- Collaborate with Data Scientists, Analysts, and DevOps teams to deliver reliable data solutions.</p><br/><p>- Monitor and troubleshoot data pipeline failures and latency issues.</p><br/><p><b>Required Skills :</b></p><br/><p>- Strong experience with Snowflake architecture, SQL, and performance tuning.</p><br/><p>- Hands-on expertise in AWS Glue, Lambda, S3, EMR, and CloudWatch.</p><br/><p>- Proficiency in Apache Spark (PySpark or Scala).</p><br/><p>- Familiarity with Snowpipe, Streams, and Tasks in Snowflake.</p><br/><p>- Knowledge of CI/CD tools and infrastructure-as-code (Terraform, CloudFormation).</p><br/><p>- Experience with version control (Git) and agile development practices</p><br/></p> (ref:hirist.tech)