Senior Data Engineer (Urgently Hiring)

FocusPoint is partnering with a forward thinking organization to hire a Senior Data Engineer who will design, build, and operate mission critical data products on Microsoft Azure. This role is ideal for an engineer who thrives in complex environments, enjoys solving business problems with data, and brings both hands on depth and architectural maturity. The position centers on building reliable pipelines, enabling analytics at scale, and elevating engineering standards across the data ecosystem., The Senior Data Engineer will own the development and operation of production grade data pipelines supporting commercial, operational, and analytical decision making. You'll work extensively with Azure Databricks, Azure SQL, Synapse, and Azure Data Factory to deliver trusted datasets, improve platform reliability, and drive best practices across the data lifecycle. This is a high impact role with visibility across technical and business teams., Build & Operate Scalable Data Pipelines

• Develop and optimize batch and streaming ingestion pipelines using Azure Data Factory, Databricks, Python, and PySpark.
• Deliver high quality datasets with clear SLAs for accuracy, timeliness, and availability.
• Create curated, reusable data assets for BI, analytics, and data science teams.

Ensure Platform Stability & Reliability

• Monitor pipeline health and lead incident response, troubleshooting, and root cause analysis.
• Establish runbooks, alerting, and operational standards for mission critical data products.
• Continuously improve performance, cost efficiency, and system resilience.

Architect Secure, Scalable Azure Solutions

• Define and enforce architectural patterns for ingestion, transformation, storage, and access.
• Implement data quality, observability, lineage, and governance practices.
• Support the evolution of a modern Azure lakehouse environment.

Partner Across the Business

• Translate business requirements into robust technical solutions.
• Collaborate with analytics teams to design semantic layers and data models aligned to KPIs and commercial processes.
• Work closely with operations, finance, and product stakeholders to support data driven decision making.

Provide Technical Leadership

• Raise engineering maturity through improved coding standards, testing, CI/CD, and DevOps practices.
• Mentor peers and contribute to architectural decisions and engineering frameworks., As a trusted staffing partner to industry-leading companies, FocusPoint provides access to roles that align with your professional goals, and we advocate for your success throughout the recruitment process. Our team understands appropriate skillsets and takes a consultative approach ensuring that each match is grounded in both experience and fit. How to Apply To ensure confidentiality and alignment with our client's hiring process, all applications must be submitted through FocusPoint. Please do not attempt to contact the client directly. Interested candidates should reach out to FocusPoint's recruitment team with any questions. About FocusPoint: FocusPoint specializes in connecting top-tier professionals with exceptional opportunities in accounting, technology, healthcare, and leadership. We prioritize building meaningful connections, ensuring candidates find roles that align with their skills, goals, and passions.

• 9+ years of data engineering experience, including 5+ years with deep Azure + Databricks expertise.
• Strong hands on experience with Databricks (Spark, Python notebooks, workflows/jobs).
• Advanced SQL skills, including Azure SQL and Synapse development with stored procedures.
• Proven delivery of production pipelines using Azure Data Factory and modern ELT/ETL patterns.
• Strong Python/PySpark for data engineering and automation.
• Experience with Azure infrastructure (storage, networking, identity/access, monitoring).
• Background in data modeling, data quality, observability, and governance.
• Expert level experience with Azure DevOps and CI/CD.

Preferred Experience

• Exposure to commercial or operational domains (e.g., pricing, contracts, scheduling, credit/risk, trading/marketing).
• Lakehouse governance (Unity Catalog), RBAC/ABAC, and standardized access patterns.
• Infrastructure as Code (Terraform/Bicep) and advanced DevOps practices.
• Familiarity with enterprise data product operating models.

Target Technology Stack

• Azure Databricks, Spark, Python
• Azure SQL, Synapse, advanced SQL
• Azure Data Factory
• Azure storage, security, monitoring
• BI/analytics consumption layers

Success Indicators (First 90 180 Days)

• Delivery of critical datasets with defined SLAs and strong data quality.
• Increased pipeline observability and reduced incident frequency.
• Adoption of standardized Azure lakehouse patterns across key business areas.