Senior Data Engineer - Remote Databricks & Data Platform

Nextech

Pittsburgh (Allegheny County)

Remote

USD 140,000 - 190,000

Full time

14 days+

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Job summary

Nextech, a data‑driven healthcare tech company, seeks a hands-on Senior Data Engineer to design and operate an enterprise data warehouse and production pipelines in Azure Databricks. You will own data domains across Bronze, Silver, and Gold layers, and ensure data quality and performance.

You will mentor engineers, enable event‑driven ingestion, optimize pipelines, and collaborate with governance, QA, analytics, and business stakeholders to deliver trusted data assets for decision making.

Qualifications

Six or more years of progressive data engineering experience.
Experience owning an enterprise data warehouse or large-scale data transformation pipelines in production with defined SLAs.
Deep, hands-on Databricks experience in production environments.
Strong experience with Delta Lake, medallion architecture, Unity Catalog, and Databricks pipeline performance optimization.
Advanced SQL skills and strong proficiency with Python and PySpark.
Ability to independently build, review, troubleshoot, and optimize complex data transformations.
Strong data warehousing experience, including dimensional modeling, harmonized data models, conformance rules, and survivorship logic.
Hands-on experience with Azure Databricks, Azure Data Lake Storage, Azure Data Factory, and CI/CD practices using Azure DevOps.
Experience operating production data pipelines, including monitoring, incident response, reliability management, and performance improvement.
Ability to learn complex, under-documented data environments and create clear, durable technical documentation.
Strong communication skills and the ability to work directly with technical, governance, quality, analytics, and business stakeholders.

Responsibilities

Design, build, and support enterprise data warehouse pipelines and data models across Bronze, Silver, and Gold layers in Databricks.
Develop ingestion patterns and Bronze-to-Silver transformations that produce clean, standardized, and reliable data.
Create dimensional and harmonized data models, including conformance, survivorship, and Gold-layer promotion rules.
Own assigned data domains in production, including data-model integrity, pipeline reliability, ingestion SLAs, incident response, and root-cause remediation.
Build and maintain Delta Lake pipelines and help transition selected workloads from batch processing to event-driven, low-latency ingestion.
Develop streaming and high-SLA ingestion patterns using technologies such as Zerobus Ingestion and Spark Declarative Pipelines.
Implement row-level reconciliation, validation checkpoints, automated quality gates, and data-contract validation throughout the data lifecycle.
Build Gold-layer tables that support Unity Catalog metric views, lineage tracking, governed access, and downstream analytics.
Optimize pipeline performance, processing latency, platform reliability, and Databricks compute costs.
Consolidate legacy transformation layers into a simplified target architecture while validating output accuracy.
Monitor pipeline health, investigate anomalies, and resolve data-reliability incidents.
Document architecture decisions, data models, transformation logic, feed SQL, and operational procedures.
Review pull requests and maintain code quality through Azure DevOps, Git, and CI/CD practices.
Mentor Data Engineers in Databricks development patterns, SQL, Python, PySpark, testing, and documentation.
Collaborate directly with data governance, quality assurance, analytics engineering, and business-facing stakeholders to clarify requirements and resolve delivery issues.