Duration <\/b> : 12 months <\/span>
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Rate Range <\/b> : Up to$85/hr on W2 depending on experience (no C2C or 1099 or sub -contract)<\/span>
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Work Authorization <\/b> : GC, USC, All valid EADs except OPT, CPT, H1B <\/span>
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Must Have: <\/b>
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• 5+ years Data Engineering
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• Airflow
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• Spark DataFrame API
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• Databricks
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• SQL
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• API integration
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• AWS
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• Python or Java or Scala
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Responsibilities <\/b> :
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• Maintain, update, and expand Core Data platform pipelines.
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• Build tools for data discovery, lineage, governance, and privacy.
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• Partner with engineering and cross -functional teams to deliver scalable solutions.
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• Use Airflow, Spark, Databricks, Delta Lake, Kubernetes, and AWS to build and optimize workflows.
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• Support platform standards, best practices, and documentation.
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• Ensure data quality, reliability, and SLA adherence across datasets.
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• Participate in Agile ceremonies and continuous process improvement.
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• Work with internal customers to understand needs and prioritize enhancements.
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• Maintain detailed documentation that supports governance and quality.
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Qualifications <\/b> :
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• 5+ years in data engineering with large -scale pipelines.
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• Strong SQL and one major programming language (Python, Java, or Scala).
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• Production experience with Spark and Databricks.
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• Experience ingesting and interacting with API data sources.
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• Hands -on Airflow orchestration experience.
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• Experience developing APIs with GraphQL.
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• Strong AWS knowledge and infrastructure -as -code familiarity.
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• Understanding of OLTP vs OLAP, data modeling, and data warehousing.
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• Strong problem -solving and algorithmic skills.
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• Clear written and verbal communication.
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• Agile/Scrum experience.
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• Bachelor’s degree in a STEM field or equivalent industry experience.
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