Azure Sr. Data Engineer

Location: Anywhere in US (Fully Remote) 

Employment Type: FTE 

Level: Experienced/Sr. Level  

GENERAL DESCRIPTION & RESPONSIBILITIES 

As a Sr. Data Engineering Consultant, you will architect, build, and optimize scalable data pipelines, data lakes, warehouses, and analytics platforms in the Microsoft ecosystem. Collaborate directly with clients to drive successful data modernization and advanced analytics projects while mentoring teams and sharing best practices. 

Key Responsibilities: 

• Architect, develop, and deploy robust, scalable data solutions using Azure Synapse, Databricks, Fabric, Data Factory, and related tools. 

• Design and optimize ETL/ELT data pipelines with Python, PySpark, and SQL for structured and unstructured data. 

• Build modern data architectures: data lakes, warehouses, lakehouses, and streaming platforms. 

• Implement and automate data ingestion, transformation, modeling, and validation within Azure and Databricks. 

• Lead end-to-end Power BI or Fabric analytics solutions, including semantic modeling, DAX, and data visualization. 

• Advice on data modernization, governance (Purview, Entra ID), and security best practices aligned with Microsoft frameworks. 

• Partner with clients and project teams, translate business requirements into actionable architectures, and communicate technical plans to stakeholders. 

• Mentor peers and guide teams on best practices, technical standards, and continuous learning in the Microsoft/Databricks ecosystem. 

• Author high-quality project, design, and technical documentation as well as support pre-sales and business development activities as needed. 

PLACEMENT CRITERIA & REQUIREMENTS 

• Bachelors in Computer Science, Engineering, or related discipline (Master’s preferred). 

• 5+ years of hands-on experience designing, building, and deploying data solutions in Microsoft Azure and Databricks. 

• Strong expertise in Python, SQL, PySpark, and modern ETL data engineering practices. 

• Advanced knowledge of Databricks, Azure Data Factory, Azure Synapse, Fabric, Azure SQL/Dataverse, and Power BI. 

• Experience with data modeling, pipeline optimization, performance tuning, and cloud-based storage (OneLake, Data Lake, CosmosDB). 

• Deep understanding of data governance, security, and compliance frameworks within Microsoft cloud. 

• Excellent communication, project leadership, and stakeholder management skills. 

DESIRED SKILLS 

• Bachelors in Computer Science, Engineering, or related discipline (Master’s preferred). 

• 5+ years of hands-on experience designing, building, and deploying data solutions in Microsoft Azure. 

• Strong expertise in Python, SQL, PySpark, and modern ETL data engineering practices. 

• Advanced knowledge of  Azure Data Factory, Azure Synapse, Fabric, Azure SQL/Dataverse, and Power BI. 

• Experience with data modeling, pipeline optimization, performance tuning, and cloud-based storage (OneLake, Data Lake, CosmosDB). 

• Deep understanding of data governance, security, and compliance frameworks within Microsoft cloud. 

• Excellent communication, project leadership, and stakeholder management skills. 

NON-TECHNICAL SKILLS 

Communication 

• Clear and effective verbal and written communication for both technical and non-technical audiences 

• Confident presentation skills, including the ability to explain complex concepts to senior clients. 

Teamwork & Leadership 

• Ability to mentor, coach, and lead cross-functional teams in collaborative environments 

• Ability to foster a problem-solving culture and contribute meaningfully to team objectives. 

Client Engagement 

• Strong sense of responsibility, accountability, and trust-building with client stakeholders. 

• Ability to manage client expectations regarding scope, timeline, and cost. 

Adaptability & Learning 

• Growth mindset and willingness to continuously improve skills and adopt new technologies. 

• Comfort in fast-paced consulting environments and ability to quickly learn new tools and concepts. 

Organization & Initiative 

• Results-oriented approach