JOBSEARCHER

Databricks Data Engineer

HomeAboutAdaptive AIIndustriesConsulting Jobs PortalContact UsHomeAboutAdaptive AIIndustriesConsulting Jobs PortalContact UsJob Description
Job Overview
Job ID: J53255Job Title:
Databricks Data Engineer
Location: Harrisburg, PA
Duration: 10 Months + Extension
Domain Exposure: Retail, Real Estate
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, L2-EAD, GC-EAD
Client: To Be Discussed Later
Employment Type:
  • W-2, 1099, C2CView All Jobs
  • Similar Jobs
  • Databricks Data Engineer - Dallas, TXAzure Databricks Engineer - Houston, TXPython Developer with Databricks - marysville, ALData Engineer - Databricks - New york, NYData Engineer Databricks / Python / Database - Jersey city, NJ
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.
Key Responsibilities: Architecture & DesignDefine 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.
Data Engineering & Implementation: Build and guide development of PySpark-based data pipelines in Databricks. Implement Delta Lake features:
  • ACID transactions.
  • Schema evolution & enforcement.
  • Time travel & versioning.
  • 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.
Collaboration & Leadership:
  • 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.Strong expertise in dbt.
  • Deep experience with Delta Lake.
  • Strong knowledge of AWS cloud services (S3, IAM, Glue, CloudWatch).Data Engineering Expertise
  • Sales data domain experience (orders, revenue, pricing, customers, products).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. Experience integrating CRM / Sales systems (e.g., Salesforce, SAP Sales data).AWS certifications or Databricks certifications.
Equal Opportunity Employer: .Apply NowEqual 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. Home|About|Adaptive AI|Industries|Consulting |Contact Us© 2008-2018, Machine Learning Technologies LLC. All Rights Reserved.