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Data Engineer with Databricks

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Onsite

Data Engineer with Databricks

Pacer Group

Data Engineer with Databricks

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonKafkaDatabricksGitData AnalysisAWSPySparkApache AirflowComplianceAzure

4 days ago

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Important information


Contract type:

Freelance / Contract

Salary:

$43 – $53 / hour

Location:

Wilmington, DE, USA

Work mode:

Onsite

Published on:

18 October 2026

What they need


Job Title: Data Engineer with Databricks

Location: Wilmington, DE

Work Arrangement: Onsite

Employment Type: Contract

Duration: 6+ Months

Pay Rate: $43.00/hr W2 | $53.00/hr C2C

Application Deadline: October 20, 2026

Domain: Banking & Financial Services

SKILLS REQUIRED

Primary (Must-Have):

  • Databricks Development | Lakehouse Architecture | Delta Lake

  • PySpark | Apache Spark | Python Programming

  • Advanced SQL Querying | Data Transformation & Validation

  • Scalable ETL / ELT Data Pipeline Design

  • Cloud Data Engineering (Azure / AWS / GCP)

Secondary (Good to Have):

  • Databricks Unity Catalog | Workflows & Cluster Optimization

  • Azure Data Factory | Apache Airflow Orchestration

  • Real-Time Data Streaming | Kafka | Spark Structured Streaming

  • Git Version Control | CI/CD Deployment Pipelines

  • Banking & Financial Services Domain Experience (Ex-JPMC Preferred)

POSITION OVERVIEW

The Data Engineer sits within the Enterprise Data & Analytics Engineering Division, reporting to the Lead Data Architect. This professional solves complex enterprise data processing challenges by designing, building, and optimizing scalable, cloud-native ETL/ELT pipelines and Lakehouse architectures. By enforcing robust data quality controls, performance tuning, and seamless data integration across systems, this role ensures reliable data delivery for critical financial reporting and business analytics.

ROLES & RESPONSIBILITIES

  • Design and develop scalable, production-grade ETL/ELT data pipelines using Databricks, PySpark, and Python.

  • Build and maintain robust data processing solutions using Delta Lake and modern Lakehouse architecture.

  • Write and optimize complex SQL queries for data transformation, reconciliation, and validation across enterprise datasets.

  • Integrate data from diverse source systems, including relational databases, APIs, cloud storage, and flat files.

  • Troubleshoot production pipeline issues, perform root-cause analysis, and optimize Spark jobs and cluster workloads for performance and cost efficiency.

BENEFITS

Medical | Dental | Vision | 401(k)

EEOC Compliance:

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment.

DISCLAIMER

AI Usage Policy: Pacer Group uses AI to assist in screening applications. Final hiring decisions are made by human recruiters based on qualifications and experience.

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