DATA ENGINEER
Key Responsibilities
- Design, develop, and optimize scalable ETL/ELT pipelines to ingest, transform, and integrate data from multiple source systems.
- Build and maintain cloud-based data platforms, data lakes, and data warehouses to support analytics and reporting.
- Develop robust SQL and Python-based data transformation logic, ensuring high performance and scalability.
- Implement data validation, reconciliation, monitoring, and quality frameworks to ensure data accuracy and reliability.
- Collaborate with business, product, analytics, and engineering teams to gather requirements and deliver data solutions aligned with business objectives.
- Develop and optimize data models, staging layers, and curated datasets for BI reporting and downstream applications.
- Integrate data from APIs, databases, cloud storage, and third-party systems using modern integration techniques.
- Troubleshoot data pipeline issues, optimize performance, and support production deployments.
- Implement data governance, security, documentation, and best practices throughout the data lifecycle.
- Participate in Agile ceremonies, code reviews, and continuous improvement initiatives.
Required Skills & Qualifications
- 10+ years of IT experience with at least 5 years of hands-on Data Engineering experience.
- Strong proficiency in SQL and Python.
- Hands-on experience with ETL/ELT development and data pipeline orchestration.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with technologies such as Databricks, Apache Spark/PySpark, Amazon Redshift, AWS Glue, Amazon S3, or equivalent cloud data services.
- Strong understanding of data warehousing, dimensional modeling, and modern data lake architectures.
- Experience working with relational databases, APIs, file-based integrations, and cloud storage.
- Knowledge of data quality, metadata management, and data governance principles.
- Experience working in Agile/Scrum environments.
- Excellent analytical, problem-solving, and stakeholder communication skills.
Preferred Qualifications
- Experience with workflow orchestration tools such as Apache Airflow or equivalent.
- Experience with CI/CD pipelines, Git, and DevOps practices for data engineering.
- Familiarity with Power BI, Tableau, or other BI tools.
- Cloud certifications (AWS, Azure, Databricks) are a plus.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.