Lead Data Engineer
Openkyber
Position: Senior Data Engineer
Experience: 10+ Years
Employment Type: Contract W2
We are looking for an experienced Senior Data Engineer with 10+ years of experience in designing, developing, and maintaining scalable data pipelines and enterprise data platforms. The ideal candidate should have strong expertise in Python, SQL, PySpark, ETL/ELT, cloud platforms, data warehousing, and modern data engineering technologies.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines for large and complex datasets.
- Develop data processing solutions using Python, PySpark, and SQL.
- Build and optimize data pipelines using tools such as AWS Glue, Informatica, Azure Data Factory, Databricks, or equivalent technologies.
- Design and implement data warehouses, data lakes, and lakehouse solutions.
- Work with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Develop data ingestion and transformation processes from structured and unstructured data sources.
- Perform data profiling, validation, cleansing, and quality checks.
- Optimize SQL queries, Spark jobs, and data pipelines for performance and scalability.
- Work with databases including Oracle, PostgreSQL, SQL Server, Teradata, Snowflake, BigQuery, or Redshift.
- Implement CI/CD processes and version control using Git, Jenkins, GitHub Actions, or Azure DevOps.
- Collaborate with Data Architects, Business Analysts, DevOps Engineers, and application teams.
- Monitor production pipelines, troubleshoot failures, and resolve data-related issues.
- Ensure data security, governance, lineage, and compliance standards are followed.
- Participate in architecture discussions, code reviews, technical documentation, and mentoring of junior engineers.
Required Skills
- 10+ years of experience in Data Engineering or related fields.
- Strong hands-on experience with Python, PySpark, and SQL.
- Strong understanding of ETL/ELT concepts and data pipeline development.
- Experience with AWS, Azure, or Google Cloud Platform cloud environments.
- Strong experience with Databricks / Spark and distributed data processing.
- Experience with Snowflake, BigQuery, Redshift, Teradata, Oracle, or PostgreSQL.
- Experience with data lakes, data warehouses, and lakehouse architecture.
- Knowledge of Kafka or other streaming technologies is preferred.
- Experience with Git and CI/CD tools.
- Strong troubleshooting, analytical, and problem-solving skills.
- Excellent communication and collaboration skills.
Preferred Skills
- Experience with Informatica PowerCenter/IICS/IDMC, Talend, AWS Glue, ADF, or similar ETL tools.
- Experience with Airflow, Control-M, or other workflow orchestration tools.
- Knowledge of Terraform and cloud infrastructure.
- Experience with Delta Lake / Delta Live Tables.
- Knowledge of data governance, metadata management, and data quality frameworks.
- Experience working in Agile/Scrum environments.
For applications and inquiries, contact:View email address on us.fitly.work
Vacancy posted 2 days ago
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