Lead Data Engineer Job at Openkyber, South Carolina

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  • Openkyber
  • South Carolina

Job Description

Senior Data Engineer Job Description:

Experience: 10+ Years

Job Type: W2 Contract Only

Job Summary We are seeking a Senior Data Engineer with 10+ years of experience in designing, developing, and supporting scalable data solutions. The ideal candidate will have strong experience with Python, SQL, ETL/ELT, cloud platforms, data pipelines, data warehousing, and distributed data processing .

Required Qualifications & Technical Skills:
  • 10+ years of experience in Data Engineering, ETL, data integration, or related technologies .
  • Strong hands-on experience with Python and advanced SQL .
  • Experience designing and developing scalable ETL/ELT data pipelines .
  • Strong understanding of data warehousing, data lakes, data modeling, and data integration concepts.
  • Experience with Apache Spark / PySpark for large-scale data processing.
  • Hands-on experience with Databricks or similar modern data platforms.
  • Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform .
  • Experience with relational databases such as SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, or similar .
  • Experience developing data ingestion and transformation processes from databases, APIs, files, and other sources.
  • Strong knowledge of data quality, validation, reconciliation, and error handling .
  • Experience with workflow orchestration tools such as Airflow, Azure Data Factory, AWS Glue, or similar .
  • Experience with Git, CI/CD, and automated deployment processes .
  • Strong troubleshooting and performance optimization skills.
  • Experience working in Agile/Scrum environments .
Responsibilities:
  • Design, develop, and maintain enterprise-scale data pipelines and integration solutions .
  • Develop complex data transformations using Python, SQL, Spark, and PySpark .
  • Build data ingestion processes from structured and unstructured data sources.
  • Design and maintain data warehouse and data lake solutions.
  • Optimize SQL queries, Spark jobs, and data pipelines for performance and scalability.
  • Implement data validation, quality checks, monitoring, and reconciliation processes.
  • Develop and manage data workflows using orchestration tools.
  • Work with cloud storage, databases, APIs, and enterprise data platforms.
  • Support production data pipelines and troubleshoot data-processing issues.
  • Implement CI/CD practices for data engineering code and deployment.
  • Collaborate with data architects, analysts, developers, QA teams, and business stakeholders.
  • Participate in technical design, code reviews, sprint planning, and other Agile activities.
  • Document data flows, technical solutions, data mappings, and operational processes.
  • Mentor junior and mid-level data engineers and contribute to data engineering best practices.
Preferred Skills:
  • Experience with Delta Lake / Lakehouse architecture .
  • Knowledge of AWS S3, Azure Data Lake, ADLS, or Google Cloud Storage .
  • Experience with Snowflake or other 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 with data governance, metadata, lineage, and security.
  • Exposure to real-time and near-real-time data processing.
Domain Knowledge:
  • Strong understanding of enterprise data integration, reporting, analytics, and data warehouse environments .
  • Experience working with large-volume transactional and analytical data.
  • Understanding of business requirements, data mapping, data transformation, and downstream reporting needs.
  • Experience working with cross-functional technical and business teams.

For applications and inquiries, contact:hirings@openkyber.com

Job Tags

Contract work

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