Senior Data Engineer

Sonny's Enterprises LLC

$120K — $150K *
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years in data engineering with expertise in Databricks and data pipelines.
  • Strong knowledge of Spark, SQL, Python, and dimensional data model design.
  • Experience with ERP systems like SAP and complex commercial domains.
  • Proven ability in creating governed datasets for BI and AI applications.
  • Solid understanding of ETL/ELT processes and data quality optimization techniques.

Responsibilities

  • Lead Databricks lakehouse execution focusing on maintainable pipelines and quality data outputs.
  • Own the implementation of common data models and design reusable datasets for analytics.
  • Design scalable data models across key operational domains including manufacturing and finance.
  • Ensure proper onboarding of new data sources for structured analytics and AI usability.
  • Implement data quality checks and optimize structured data assets for performance.
  • Provide technical leadership for engineering standards and backlog execution in Databricks.

Benefits

  • 100% employer paid medical plan.
  • 401(k) match available.
  • Optional medical, dental, and vision plans offered.
  • Flexible spending accounts for added financial flexibility.
  • Short-term and long-term disability insurance included.
  • Life insurance coverage provided.
Full Job Description
Overview

The Senior Data Engineer is the lead delivery role for structured data engineering in Databricks. This role owns lakehouse execution across bronze, silver, and gold; common data model implementation; SAP and manufacturing data modeling; curated outputs for reporting and AI/BI; and the transformation layer that supports forecasting, process automation, and internal applications. This role is the core engineering owner for turning source data into governed, reusable, high-value data products and brings working knowledge of source integration patterns so engineering decisions remain practical from ingestion through consumption.

 

Works closely with architecture, BI, master data, product, and application teams to turn business requirements into trusted datasets and scalable data products. Coordinates with integration-focused resources on source readiness, connector behavior, and new source onboarding.

 

Responsibilities

• Lead Databricks lakehouse execution across bronze, silver, and gold with a focus on maintainable Lakeflow-driven pipelines and high-quality curated outputs.• Own common data model implementation, conformed dimensions, fact design, and reusable gold datasets for reporting, forecasting, and AI/BI consumption.• Design and build scalable data models for SAP, manufacturing, finance, sales, supply chain, and operational domains.• Partner on source onboarding and ensure new data is shaped into governed medallion outputs that are usable for analytics and AI.• Implement data quality checks, reconciliation logic, documentation, and performance optimization across structured data assets.• Provide technical leadership for engineering backlog execution, code quality, testing discipline, and repeatable delivery standards in Databricks.

 

Qualifications

• 7+ years of experience in data engineering with strong ownership of Databricks, data modeling, and production data pipelines.• Deep experience with Spark, SQL, Python, medallion architecture, and dimensional or conformed data model design.• Experience working with SAP or comparable ERP data and complex manufacturing, finance, supply chain, or commercial subject areas.• Experience building governed curated datasets for BI, forecasting, and AI enablement.• Strong understanding of ETL/ELT patterns, source-to-target mapping, data quality, and performance optimization.

• Experience with Lakeflow, Fivetran-fed source patterns, Unity Catalog governance, and Power BI semantic consumption, preferred. • Experience supporting AI/BI readiness, trusted metrics, and curated outputs for natural-language analytics, preferred. • Exposure to observability, CI/CD, and testing frameworks in Databricks, preferred.

 

We offer 100% employer paid medical plan. Other optional benefit programs are available to our employees and their families which include: 401(k) match, additional medical plans, dental, vision, flex spending account, short-term and long-term disability & life insurance coverage.

 

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