Job
Description
Key Responsibilities Design, build, and maintain robust ETL/ELT pipelines and data workflows. Develop and optimize data architectures for performance and scalability. Implement data quality and validation checks to ensure reliable data delivery. Collaborate with data analysts, scientists, and stakeholders to understand data needs. Integrate data from various sources including APIs, databases, cloud platforms, and third-party providers. Maintain and enhance data lake/data warehouse environments (e.g., AWS Redshift, Google BigQuery, Snowflake). Ensure data privacy and security compliance with internal and external regulations (e.g., GDPR, HIPAA). Monitor and troubleshoot data pipeline failures and performance bottlenecks. Required Qualifications Bachelorâs or Masterâs degree in Computer Science, Engineering, Information Systems, or a related field. 8+ years of experience as a Data Engineer or in a similar role. Strong proficiency in SQL and data modeling. Experience with data pipeline tools (e.g., Apache Airflow, dbt, Luigi). Proficient in Python, Scala, or Java. Familiarity with cloud platforms such as AWS, GCP, or Azure. Experience with data warehouses and big data technologies (e.g., Spark, Hive, Kafka). Understanding of data governance and best practices for data quality. Skills: kafka,data architectures,data,scala,data modeling,dbt,data privacy,data quality,java,spark,aws redshift,cloud platforms,data lake,hive,gcp,apis,data validation,data workflows,big data,azure,apache airflow,data security,aws,data warehouse,data governance,snowflake,google bigquery,cloud,sql,luigi,apache,databases,etl,python,elt Show more Show less
