Data Engineering & Warehousing Engineer
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Key skills for this role
About the Role
Seeking a skilled Data Engineering & Warehousing Engineer with 3-11 years of experience to design, develop, and maintain scalable data platforms and enterprise data warehouse solutions.
Key Skills for This Role
Responsibilities
- Design, develop, and optimize scalable ETL/ELT pipelines for structured and unstructured data
- Build and maintain enterprise data warehouses, data lakes, and modern data platforms
- Develop real time and batch data processing solutions
- Integrate data from multiple internal and external sources while ensuring data quality and governance
- Collaborate with Data Scientists, BI Developers, and business stakeholders to support analytical requirements
- Optimize data storage, query performance, and pipeline reliability
- Implement data security, monitoring, and governance best practices
- Troubleshoot and resolve data pipeline and platform issues
- Participate in architecture discussions and contribute to data platform modernization initiatives
Requirements
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or related field
- 3–11 years of professional experience in Data Engineering, Data Warehousing, or Big Data technologies
- Hands on experience with Google BigQuery, Dataflow, Dataproc, Pub/Sub
- Experience with Azure Synapse and Azure Data Factory
- Experience with Amazon Redshift and AWS Glue
- Strong experience with Apache Spark and Apache Kafka
- Hands on experience with dbt or Oracle Data Integrator (ODI)
- Strong experience with Oracle or PostgreSQL
- Expertise in SQL, relational database design, performance tuning, and query optimization
- Strong programming and scripting skills using SQL, Python, or similar languages
- Experience with data modeling, data governance, metadata management, and data quality frameworks
- Experience working in Agile/Scrum development environments
Full Job Posting
Job Overview
- We are seeking a highly skilled Data Engineering & Warehousing Engineer with 3–11 years of experience to design, develop, and maintain scalable data platforms and enterprise data warehouse solutions.
- The ideal candidate will have hands on expertise in building ETL/ELT pipelines, data integration, cloud based data platforms, and big data processing technologies.
- You will play a key role in enabling reliable, high performance analytics and business intelligence solutions.
Key Responsibilities
- Design, develop, and optimize scalable ETL/ELT pipelines for structured and unstructured data
- Build and maintain enterprise data warehouses, data lakes, and modern data platforms
- Develop real time and batch data processing solutions
- Integrate data from multiple internal and external sources while ensuring data quality and governance
- Collaborate with Data Scientists, BI Developers, and business stakeholders to support analytical requirements
- Optimize data storage, query performance, and pipeline reliability
- Implement data security, monitoring, and governance best practices
- Troubleshoot and resolve data pipeline and platform issues
- Participate in architecture discussions and contribute to data platform modernization initiatives
Required Technical Skills
- Cloud Data Platforms: Google BigQuery, Dataflow, Dataproc, Pub/Sub; Azure Synapse, Azure Data Factory; Amazon Redshift, AWS Glue
- Data Processing & Streaming: Apache Spark, Apache Kafka
- Data Transformation: dbt or Oracle Data Integrator (ODI)
- Databases & Data Warehousing: Oracle or PostgreSQL; SQL, relational database design, performance tuning, query optimization
- Data Engineering: data modeling, data governance, metadata management, data quality frameworks; dimensional modeling and modern data warehouse architectures
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field
- 3–11 years of professional experience in Data Engineering, Data Warehousing, or Big Data technologies
- Strong programming and scripting skills using SQL, Python, or similar languages
- Excellent analytical and problem solving abilities
- Experience working in Agile/Scrum development environments
Preferred Skills
- Experience with cloud native data lake and lakehouse architectures
- Knowledge of CI/CD pipelines and Infrastructure as Code (IaC)
- Familiarity with containerization technologies such as Docker and Kubernetes
- Experience supporting machine learning and analytics workloads
- Cloud certifications on AWS, Microsoft Azure, or Google Cloud Platform are a plus
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