Senior Data Engineer
Raas Infotek
Job Summary We are seeking a highly experienced Senior Data Engineer with 12+ years of expertise in designing, building, and maintaining scalable data platforms and ETL/ELT pipelines. The ideal candidate should have strong experience with cloud technologies, big data frameworks, data warehousing, and modern data engineering tools. The candidate will work closely with business stakeholders, data scientists, analysts, and application teams to deliver reliable, high-performance data solutions. Experience 12+ Years Location Texas (Onsite/Hybrid) Employment Type W2 Required Skills 12+ years of experience in Data Engineering and Data Warehousing Strong SQL, PL/SQL, and database optimization skills Python, Scala, or Java programming ETL/ELT development using Informatica, Talend, SSIS, or Azure Data Factory Cloud Platforms: AWS, Azure, or Google Cloud Platform Snowflake, Redshift, BigQuery, or Azure Synapse Apache Spark, PySpark, Hadoop ecosystem Databricks Apache Kafka or event-driven data pipelines Airflow or similar workflow orchestration tools Data Lake and Data Warehouse architecture Git, CI/CD, DevOps practices Docker and Kubernetes Strong understanding of Data Modeling (Star/Snowflake Schema) Agile/Scrum methodology Preferred Skills AWS Glue Terraform Delta Lake dbt Power BI or Tableau Machine Learning data pipelines Data Governance Master Data Management (MDM) Apache Iceberg or Delta Lake Streaming technologies Responsibilities Design and implement scalable ETL/ELT pipelines. Develop high-performance data ingestion frameworks. Build and maintain enterprise data lakes and data warehouses. Optimize SQL queries and data processing jobs. Design batch and real-time data pipelines using Spark and Kafka. Work with Snowflake, Databricks, Redshift, or Synapse. Collaborate with Data Scientists and BI teams. Ensure data quality, security, and governance. Implement CI/CD pipelines for data engineering projects. Monitor production jobs and troubleshoot performance issues. Mentor junior engineers and conduct code reviews. Work closely with business stakeholders to gather requirements. Required Technologies Python SQL PySpark Apache Spark Databricks Snowflake AWS (S3, Glue, EMR, Lambda, Redshift) Azure Data Factory Azure Synapse Google Cloud Platform BigQuery Kafka Airflow dbt Docker Kubernetes Git Jenkins/GitHub Actions Nice to Have AI/ML data engineering experience Generative AI integration Vector Databases Data Mesh architecture Lakehouse architecture Healthcare, Banking, or Retail domain experience Education Bachelor''s or Master''s degree in Computer Science, Information Technology, Engineering, or a related field. #J-18808-Ljbffr
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