Databricks Data Engineer

Quantum Technologies. LLC; Harrisburg (Dauphin County); On-site; USD 83,000 - 124,000; Part time

Job summary

Quantum Technologies. LLC is seeking a Databricks Data Engineer to lead the design and implementation of a scalable Sales Data Platform on Databricks running on AWS, based in Harrisburg, PA.

This contract role (C2C/1099) spans 10 months with a bill rate of $75/hour. You will build PySpark pipelines, implement Bronze/Silver/Gold Lakehouse architecture, ensure data quality and governance, and drive performance, cost optimization, and CI/CD for notebooks and jobs.

Qualifications

• 8+ years in Data Engineering / Data Architecture roles.
• 4+ years hands-on experience with Databricks.
• Strong expertise in PySpark & Spark SQL.
• Deep experience with Delta Lake.
• Strong knowledge of AWS cloud services (S3, IAM, Glue, CloudWatch).
• Strong understanding of Fact & dimension modelling and SCD Type 1/2.
• Experience handling high-volume, high-velocity datasets.

Responsibilities

• Lead design and implementation of scalable Sales Data Platform on Databricks (AWS).
• Build PySpark-based data pipelines and medallion architecture (Bronze/Silver/Gold).
• Define end-to-end Lakehouse architecture and data modelling standards for Sales data domains.
• Implement CDC, incremental processing, and robust error handling.
• Develop CI/CD pipelines for Databricks notebooks and jobs and mentor engineers.

Skills

Data engineering

Data architecture

PySpark & Spark SQL

Delta Lake

AWS cloud services

Data modelling

SCD Type 1/2

Large-scale data processing

Tools

Databricks

AWS S3

AWS IAM

AWS Glue

CloudWatch

Delta Lake

Job description

Job Title :Databricks Data Engineer
Job Type : C2C/1099 Contract
Location : Harrisburg, PA
Duration :10 months
Bill Rate : $75/Hr on c2c

Role Summary

• We are seeking a Databricks Engineer to lead the design and implementation of a scalable Sales Data Platform as part of the One Data initiative on Databricks running on AWS.
• The role is hands-on and architecture-driven, focused on data ingestion, transformation, modelling, and optimization using modern Lakehouse patterns.
• The architect will work closely with data engineers, source system teams, and downstream consumers to deliver high-quality, governed, and performance-optimized sales datasets.
• Define end-to-end Lakehouse architecture on Databricks (AWS) for Sales data domains.
• Design medallion architecture (Bronze / Silver / Gold) aligned with One Data standards.
• Establish data modelling standards for Sales facts, dimensions, hierarchies, and aggregations.
• Define scalable ingestion patterns for batch and incremental loads.
• Drive performance, scalability, and cost optimization best practices.
• Build and guide development of PySpark-based data pipelines in Databricks.
• ACID transactions.
• Design and optimize large-scale joins, aggregations, and window functions.
• Implement CDC and incremental processing using watermarking and change detection.
• Ensure idempotent, restart able, and fault-tolerant pipelines.

AWS & Platform Integration

• Architect solutions using AWS services:
  • Amazon S3 (data lake storage).
  • IAM (security & access control).
  • AWS Glue / Glue CatLog.
  • CloudWatch (monitoring & logging).
• Optimize Databricks cluster configurations (job vs all-purpose clusters).
• Implement secrets management and secure connectivity patterns.

Data Quality, Governance & Reliability

• Define and implement data quality checks and validations.
• Ensure data lineage and metadata capture.
• Implement error handling, auditing, and reconciliation frameworks.
• Support data governance and access control requirements.

DevOps & Operational Excellence

• Implement CI/CD pipelines for Databricks notebooks and jobs.
• Enforce code versioning, reviews, and deployment standards.
• Design monitoring, alerting, and SLA tracking for pipelines.
• Support production stabilization and performance tuning.
• Act as technical lead / mentor for Databricks data engineers.
• Collaborate with:
  • Source system teams (Sales, CRM, ERP).
  • Data consumers (analytics, downstream apps).
  • Cloud/platform teams.
• Translate business requirements into robust technical designs.

Required Skills & Experience

Core Technical Skills

• 8+ years in Data Engineering / Data Architecture roles.
• 4+ years hands-on experience with Databricks.
• Strong expertise in PySpark & Spark SQL.
• Deep experience with Delta Lake.
• Strong knowledge of AWS cloud services (S3, IAM, Glue, CloudWatch).
• Strong understanding of:
  • Fact & dimension modelling.
  • Slowly Changing Dimensions (SCD Type 1 / 2).
  • Large-scale data processing patterns.
• Experience handling high-volume, high-velocity datasets.

Platform & Operational Skills

• Databricks job orchestration and scheduling.
• Cluster sizing and performance tuning.
• CI/CD for data platforms.
• Strong troubleshooting and debugging skills.

Nice-to-Have

• Experience with enterprise One Data / Data Mesh programs.
• Exposure to real-time or near-real-time ingestion patterns.
• AWS certifications or Databricks certifications. Equal Opportunity Employer : .

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.