Data Engineer
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Technology Category
Data Engineering
Seniority / Level
Level I
Experience Required
2–4 years
Domain / Industry
US Healthcare
Primary Technology Stack
SQL
Secondary Technology Stack
ETL/ELT frameworks & tools
Cloud / Infrastructure
AWS / GCP / Azure (cloud-based data services)
Database / Data Technologies
SQL, data handling, ETL/ELT-based pipelines
Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines using SQL & some Python; ensure good data quality, integrity, and availability for downstream analytics and product workflows; collaborate with customers to gather requirements; troubleshoot and optimize data workflows and pipelines for performance and reliability
Must-Have Skills / Experience
Excellent SQL, experience on cloud environments (AWS, GCP, or Azure); Python and Dashboarding (PowerBI/Tableau) experience are good to have; experience on ETL/ELT frameworks and tools, performance optimization, and debugging skills; 3–5 years of experience in data engineering; Bachelor's degree in Computer Science, Engineering or related field.
Job ID: 152255525
Skills:
snowflake , Aws Lambda, PostgreSQL, Pyspark, Microsoft Sql Server, Shell Scripting, Jira, SSIS, Sql, Apache Airflow, Numpy, Git, Confluence, Pandas, Docker, AWS IAM, Python, Aws S3, dbt
Skills:
Amazon Redshift, Snowflake Data Warehouse, AWS S3 Simple Storage Service, AWS DynamoDB
Skills:
Pyspark, Aws Lambda, AWS Glue, AWS Athena, Sql, Apache Airflow, Kinesis, Amazon Redshift, Python, AWS, Etl, dbt Core, Iceberg
Skills:
S3, Github, Pyspark, Kafka, Lambda, Docker, Shell scripting, Python, Spark SQL, Hadoop, Scala, Big Data, Emr, Redshift, Sql, Hive, ECS, Spark, Cloudera, Etl, Airflow, AWS Step Functions, HDFS, EKS, Glue
Skills:
Spark SQL, Azure Data Factory, Pyspark, Databricks, Python, Sql, Azure DevOps
