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Data Engineer (Databricks / Spark)

Job

Savantys Solutions

Columbus, OH (In Person)

$124,800 Salary, Full-Time

Posted 4 days ago (Updated 2 days ago) • Actively hiring

Expires 7/18/2026

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Job Description

Data Engineer (Databricks / Spark) Savantys Solutions Columbus, OH Job Details Full-time | Contract From $60 an hour 6 hours ago Qualifications Data model design Commercial use (data warehousing systems) Performance tuning Databricks Data Integration (Data management) Azure Cloud data warehouses Data modeling projects DevOps Spark System performance optimization Scalable systems Snowflake SQL Data Architecture Design (Architecture design skills) AWS ETL process automation Airflow Scala Version control systems Scalability System tuning Data performance optimization Python Database software proficiency
Full Job Description Subject:
Data Engineer (Databricks / Spark) Data Engineer (Databricks / Spark)
Location:
Columbus, OH (5 Days Onsite)
Employment Type:
W2 Only Job Description We are seeking an experienced Data Engineer with strong expertise in Databricks and Apache Spark to join a high-performing data engineering team supporting enterprise-scale data initiatives at JPMC. The ideal candidate will have hands-on experience building scalable data pipelines, optimizing Spark workloads, and working with large datasets in cloud-based environments. Required Skills 7+ years of experience in Data Engineering and Big Data technologies. Strong hands-on experience with Databricks and Apache Spark (PySpark/Scala Spark) . Expertise in designing, developing, and optimizing large-scale ETL/ELT pipelines. Strong experience with Python and SQL. Experience working with cloud platforms such as AWS , Azure , or GCP . Hands-on experience with Delta Lake, Data Lake architecture, and data modeling concepts. Experience with workflow orchestration tools such as Airflow or similar. Strong understanding of data warehousing concepts and performance tuning. Experience with version control systems such as Git. Ability to troubleshoot and optimize Spark jobs for performance and scalability. Responsibilities Design, develop, and maintain scalable data pipelines using Databricks and Spark. Build and optimize batch and real-time data processing solutions. Collaborate with business stakeholders, architects, and development teams to understand data requirements. Perform data ingestion, transformation, cleansing, and validation activities. Monitor and troubleshoot production data pipelines. Implement data quality, governance, and security best practices. Optimize Spark jobs and Databricks clusters for performance and cost efficiency. Participate in code reviews and ensure adherence to development standards. Preferred Qualifications Experience working in financial services or banking environments. Familiarity with JPMC data platforms and enterprise data ecosystems. Experience with Kafka, Snowflake, or other modern data technologies. Knowledge of CI/CD processes and DevOps practices. Databricks or Cloud certifications are a plus.
Pay:
From $60.00 per hour
Work Location:
In person