A.C.Coy Company
51 - 200 employees
Founded 1986
💼 Consulting
📣 Marketing
📦 Logistics
Consulting • Marketing • Logistics
A. C. Coy Company is a specialized recruitment agency based in Pittsburgh, PA, that focuses on connecting professionals with job opportunities in IT, engineering, finance, and sales. Since its inception in 1986, the company has been committed to acting in the best interests of clients and candidates, offering contract, contract-to-hire, and permanent placement services. A. C. Coy aims to make successful career designs possible for job seekers while providing top talent to businesses across the Tri-State area and beyond.
Databricks Migration Engineer
Job not on LinkedIn
🕒 September 30
Where this job comes from
Posted on A.C.Coy Company's careers page ↗, not through a job board
First seen by Remote Rocketship September 30
Still open on A.C.Coy Company's site. Checked 50 minutes ago.
A.C.Coy Company
51 - 200 employees
Founded 1986
💼 Consulting
📣 Marketing
📦 Logistics
Consulting • Marketing • Logistics
A. C. Coy Company is a specialized recruitment agency based in Pittsburgh, PA, that focuses on connecting professionals with job opportunities in IT, engineering, finance, and sales. Since its inception in 1986, the company has been committed to acting in the best interests of clients and candidates, offering contract, contract-to-hire, and permanent placement services. A. C. Coy aims to make successful career designs possible for job seekers while providing top talent to businesses across the Tri-State area and beyond.
📋 Description
• Lead the technical migration from legacy SQL Server stored procedures and ADF pipelines to Databricks Lakehouse (Delta Lake) • Translate relational data warehousing paradigms into scalable, distributed Lakehouse frameworks across Bronze, Silver, and Gold layers • Design reusable ETL/ELT frameworks using PySpark, Delta Live Tables, and Databricks Workflows • Architect and refine Gold Layer dimensional models and star schemas for Power BI performance • Optimize Databricks SQL Warehouses for high-concurrency, low-latency Power BI queries • Implement Z-Ordering, data skipping, liquid clustering, and materialized views • Define governance standards for cluster sizing, auto-scaling, and serverless SQL compute • Monitor Databricks Unit consumption and identify cost-saving opportunities • Establish Delta Lake partitioning and file size management practices • Design and implement Unity Catalog data security models • Enforce row-level and column-level security policies • Align Lakehouse security with Azure Active Directory/Microsoft Entra ID and RBAC standards • Serve as primary technical lead through pair-programming sessions, workshops, and code reviews • Create technical documentation, architecture diagrams, design patterns, and optimization playbooks • Build knowledge transfer processes for post-migration team self-sufficiency • Communicate with technical and non-technical audiences • Complete tasks in an organized, timely, and detail-oriented manner
🎯 Requirements
• Bachelor's degree or higher from an accredited college or university in Computer Science, Engineering, or a related technical field • 5+ years of experience in Data Engineering, Data System Development or related roles • 5+ years of experience with Cloud platforms (e.g. Azure, AWS, GCP) • 1+ year leading complex, cross-functional data projects and technical teams • Experience with Databricks Lakehouse, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms • Experience with data warehousing, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark • Excellent communication skills • Must be a US Citizen and be able to obtain a Position of Public Trust Clearance • Must have resided in the US for the last 5 years and not have traveled outside the US for a combined total of 6 months or more in last 5 years
🏖️ Benefits
• Contract-to-Hire position • Remote work arrangement • East Coast time zone candidates preferred
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