Senior Data Engineer

Raas Infotek LLC

United States

6 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Airflow Amazon Web Services Microsoft Azure BigQuery Continuous Integration Data Architecture Data Validation Information Engineering Extract Transform Load (ETL) Data Transformation Data Warehousing Python (Programming Language)

+25 more

Performance Tuning Software Deployment SQL Databases Teradata SQL Workflow Management Systems Enterprise Data Management Google Cloud Cloud Platform System Azure Data Factory Snowflake Apache Spark Git Data Lakes Pyspark Information Technology AWS Glue Apache Kafka Spark Streaming Terraform Azure Synapse Analytics Data Pipelines Docker Jenkins Amazon Redshift Databricks

Job description

Design and develop scalable batch and real-time data pipelines.
Build and optimize cloud-based data platforms and ETL/ELT solutions.
Develop complex data transformations using Python, SQL, and PySpark.
Perform data quality checks, troubleshooting, and performance optimization.
Collaborate with architects, data scientists, analysts, and business teams.
Support production deployments and resolve complex data pipeline issues.

Requirements

We are looking for a highly experienced Senior Data Engineer with 10+ years of experience in designing and developing scalable data solutions and enterprise data platforms., * 10+ years of experience in Data Engineering / ETL

Strong hands-on experience with Python, SQL, and PySpark
Strong experience with Databricks, Apache Spark, and Delta Lake
Expertise in AWS, Azure, or Google Cloud Platform cloud platforms
Experience with Snowflake, Redshift, BigQuery, Synapse, Teradata, or similar data warehouses
Strong knowledge of ETL/ELT, data pipelines, data modeling, and data warehousing
Experience with Apache Airflow, Azure Data Factory, AWS Glue, or similar orchestration tools
Experience with Kafka / Spark Streaming is preferred
Knowledge of CI/CD, Git, Jenkins/Azure DevOps, Docker, and Terraform is a plus
Experience with CDC, SCD, partitioning, performance tuning, and data quality
Strong understanding of Data Lake, Data Warehouse, and Lakehouse architecture
Ability to lead technical discussions, perform design reviews, and mentor junior engineers, Education: Bachelor’s degree in Computer Science, IT, Engineering, or related field preferred.