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Lead Data Engineer

Openkyber

Senior Data Engineer Job Description Job Title: Senior Data Engineer

Experience: 12+ Years

Job Type: W2 Contract

Job Summary

We are seeking a highly experienced Senior Data Engineer with 12+ years of experience in designing, developing, and maintaining scalable data platforms and data pipelines. The ideal candidate will have strong hands-on expertise in Python, SQL, Spark, Databricks, cloud technologies, ETL/ELT, data warehousing, and data integration .

Responsibilities
  • Design, develop, and maintain scalable ETL/ELT data pipelines for enterprise applications.
  • Develop complex data transformation and processing workflows using Python, SQL, and Apache Spark .
  • Build and optimize data pipelines using Databricks and PySpark .
  • Design and implement data solutions on AWS, Azure, or Google Cloud Platform cloud platforms.
  • Develop data ingestion processes from databases, APIs, files, and other structured/unstructured sources.
  • Implement data quality, validation, reconciliation, and monitoring processes.
  • Design and optimize data warehouses, data lakes, and lakehouse architectures .
  • Work with relational and NoSQL databases to support data engineering requirements.
  • Perform performance tuning and optimization of SQL queries, Spark jobs, and data pipelines.
  • Implement orchestration using Apache Airflow, Azure Data Factory, AWS Glue, or similar tools .
  • Develop reusable frameworks and components for data ingestion and transformation.
  • Integrate data engineering solutions with CI/CD pipelines and DevOps processes.
  • Implement data security, access controls, encryption, and governance best practices.
  • Troubleshoot production data pipelines and resolve data processing issues.
  • Collaborate with data architects, analysts, data scientists, application developers, and business stakeholders.
  • Participate in Agile/Scrum ceremonies and contribute to technical design and architecture discussions.
  • Mentor junior and mid-level data engineers and provide technical guidance.
Required Skills
  • 12+ years of experience in Data Engineering, ETL, or related data technologies.
  • Strong hands-on experience with Python and SQL .
  • Extensive experience with Apache Spark / PySpark .
  • Strong experience with Databricks and Delta Lake.
  • Experience building enterprise-scale ETL/ELT pipelines .
  • Strong knowledge of data warehousing concepts, dimensional modeling, and data lake architectures.
  • Experience with one or more cloud platforms: AWS, Azure, or Google Cloud Platform .
  • Experience with databases such as SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, or similar .
  • Experience with workflow orchestration tools such as Airflow, Azure Data Factory, AWS Glue, or similar .
  • Strong understanding of batch and near-real-time data processing.
  • Experience with Git, CI/CD, Jenkins, Azure DevOps, or GitHub Actions .
  • Strong understanding of data quality, data validation, and performance optimization.
  • Excellent analytical, troubleshooting, and communication skills.
Preferred Skills
  • Experience with Azure Data Lake, AWS S3, ADLS, or Google Cloud Storage .
  • Experience with Snowflake or other modern cloud data warehouses.
  • Knowledge of Kafka, Event Hubs, or other streaming technologies .
  • Experience with Terraform or Infrastructure as Code .
  • Knowledge of Docker and Kubernetes.
  • Experience implementing data governance, metadata management, and lineage .
  • Experience working with large-scale distributed data environments.
  • Knowledge of Medallion Architecture (Bronze, Silver, Gold) .
  • Experience with real-time/streaming data pipelines.
  • Experience in designing highly available and fault-tolerant data platforms.

For applications and inquiries, contact:View email address on us.fitly.work

Vacancy posted 2 days ago
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