Azure Data Engineer- Lead

Description

Please note:

No agencies or staffing firms, please. We are not accepting unsolicited candidate submissions and request that agencies do not contact our employees or representatives regarding recruiting services for this role.

• Engagement Type: Contract-C2C or W-2 hourly/temporary
• Expected Commitment: 40 hours per week, Monday-Friday
• Work Schedule: Must work East Coast hours
• Initial Term: Three months, with potential to extend
• 100% Remote: Ideal candidate resides in NH, MA, RI,

Spyglass MTG is seeking experienced Lead Data Engineers who are “thinkers” and can mentor

junior developers while extending an existing codebase and building team proficiency in

Microsoft Fabric and Pyspark Python including class development and structured streaming.

Why Spyglass MTG?

• Exclusive focus on Microsoft technologies for more than 12 years
• 90% of our business comes from repeat customers
• 80% of our new business comes through Microsoft
• Five Microsoft Solutions Partner badges and 10 Advanced Specializations
• Member of Microsoft’s Partner Advisory Council for Data and AI
• Microsoft Fabric Voice member

Description:

As a Lead Azure Data Engineer, you will work as part of our Azure Data and Analytics practice by leading the design, development, and delivery of modern cloud data solutions for our clients. We are looking for an experienced Data Engineer who can provide technical leadership across the full data engineering lifecycle, including collecting, aggregating, storing, reconciling, governing, and operationalizing data in Azure in support of client business decisions. You will lead the design and implementation of scalable data pipelines, data streams, data models, and data service APIs on Azure that power data-driven portals, analytics platforms, reporting solutions, and insight tools. You will be accountable for solution quality, technical direction, delivery execution, and mentoring other data engineers while partnering with client stakeholders to translate business needs into reliable, secure, and maintainable data solutions. You will play a lead role in analyzing business, functional, and technical issues and delivering innovative Analytics solutions on Azure at enterprise data scale.

Candidate Expectations:

· Lead the design, development, testing, deployment, and support of scalable Azure data engineering solutions.

· Own technical approaches for data transformation, data modeling, metadata management, dependency management, workload orchestration, and production-quality data pipelines.

· Provide hands-on engineering leadership using SQL, Python, Scala, C#, R, or related languages as appropriate for client solutions.

· Guide architecture and delivery decisions across Azure Data Factory, Azure Synapse, Azure Data Lake, Azure SQL, Databricks, streaming, APIs, Azure Functions, and related services.

· Partner with business and technical stakeholders to define requirements, assess tradeoffs, and translate business needs into durable data platform designs.

· Lead requirements analysis, solution design, prototyping, estimation, implementation planning, and technical documentation.

· Establish and promote engineering standards for code quality, testing, CI/CD, version control, monitoring, security, performance, and maintainability.

· Mentor and support junior and mid-level engineers, review solution designs and code, and help raise the overall technical capability of delivery teams.

· Serve as a trusted technical advisor to clients and project teams, proactively identifying risks, dependencies, delivery issues, and improvement opportunities.

Requirements

Basic Qualifications:

· 8+ years of total experience in data engineering, data architecture, data warehousing, analytics engineering, or related roles.

· 4+ years of hands-on experience designing and delivering cloud data solutions using Azure SQL, Azure Synapse, Azure Data Lake, Azure Data Factory, Databricks, or comparable cloud data services.

· 4+ years of experience developing, deploying, testing, and supporting production data pipelines, data models, and integration workflows.

· 3+ years of experience leading technical workstreams, solution design activities, or delivery teams in client-facing or enterprise environments.

· 3+ years of experience with data integration platforms such as Azure Data Factory, Synapse Pipelines, SSIS, Databricks, Spark, Hadoop, or comparable tools.

· Strong working experience with SQL Server, modern data warehouses, lakehouse architectures, dimensional modeling, and analytics delivery patterns.

· Advanced programming experience with SQL and at least one additional language such as Python, Scala, C#, or R.

· Experience with DevOps, DataOps, CI/CD, version control, automated testing, deployment practices, and operational support for production data solutions.

Preferred Qualifications:

· 5+ years of experience with Azure Data Factory, Azure Synapse, Databricks, Microsoft Fabric, Azure Data Lake, or other modern cloud data platform services.

· 3+ years of experience leading code deployment, version control, DevOps, DataOps, monitoring, and release management practices for data solutions.

· 5+ years of advanced experience with SQL, Python, Scala, C#, R, or similar data engineering languages.

· Experience designing enterprise-scale data platforms, lakehouse solutions, data warehouses, semantic models, and reusable integration patterns.

· Experience leading client workshops, technical discovery sessions, architecture reviews, and delivery planning discussions.

· Experience mentoring engineers, conducting code reviews, setting delivery standards, and providing technical oversight across multiple workstreams.

· Microsoft data engineering, Azure, Databricks, Fabric, or related cloud certification preferred.

Benefits:

Medical, Vision and Dental Plans

Life and Disability Insurance

Open PTO Policy

Holiday PTO

Paid training certification

Bonus plan

401k

Flexible working arrangements

& more

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, transgender status, national origin, citizenship, age, disability or protected veteran status.