Azure Data Engineer

KEY RESPONSIBILITIES:

Design, develop, implement, analytics solutions/data products on Microsoft Azure Synapse Analytics Platform

Develop ETL/ELT processes to collect and integrate data from various sources. Ensuring data quality and data pipeline performance for large volume data ingestion

Utilize data preparation, integration, storage & analytics tools within the Azure landscape

Drive toward automation of repeatable data prep tasks to minimize manual data management processes

Partner with business unit IT teams to gather and document analytics solution requirements

Document and provide solution options and recommendations for analytics solutions

Collaborate and partner with cloud service providers, data science, data governance and other IT and business teams in the process of delivering analytics solutions

Participate in MPC's scaled agile framework for data engineering product delivery by participating in all relevant tasks and ceremonies

Provide trouble shooting, analysis and resolutions on existing solutions for routine production support issues as well as major/minor enhancements.

Adhere to MPCs change management process for solution deployment within the landscape

EDUCATION AND EXPERIENCE:

Bachelor's degree in computer science, Computer Engineering, Software Engineering, Information Systems, or related field.

Minimum 8-10 years of hands-on experience in building data pipelines, data models and maintaining/supporting enterprise data warehouse solutions

Experience in scaled agile framework for data engineering product delivery

Microsoft Azure certifications in various analytics technologies is a plus

Working knowledge/familiarity with Oil & Gas industry processes is a plus

SKILLS:

Must have strong experience with SQL, data modeling, data warehouse and medallion architecture as a data engineer

Must have strong experience building data products using Azure Data Lake Storage, Azure Synapse Analytics for data warehousing, Azure Spark Pools, Databricks Notebooks, Cosmos DB, CDC tools, Python, DevOps, Cl/CD

Familiarity with data integration tools (e.g. Qlik Replicate) and with data modeling tools (e.g. Erwin) is a plus

Familiarity with data lake/warehouse medallion architecture and concepts of Unified Data Models

Strong hands-on experience with ingesting data from a variety of structured and unstructured, on-premises and Saas sources is a must

Strong problem-solving skills as it relates to data ingestion, modeling, validation is a must

Strong communications skills and ability to interact with technical and non-technical business stakeholders is a must

Working experience and exposure to visualization tools such as Microsoft PowerBI, Tableau desired.

Familiarity with Scaled Agile, DevOps, Scrum, and ITIL concepts is a plus

Experience with Microsoft SSIS, SSRS, SSAS is a plus

Experience with ServiceNow, Azure DevOps, ADO is a plus

COMPETENCIES:

Strong communication and presentation skills - Ability to present and communicate with technical and non-technical stakeholders at different levels within IT & business departments during the various stages of solution design, development and implementation.

Collaboration & Building Partnerships - Developing and leveraging relationships within and across work groups to achieve results.

Drive for Results - Taking ownership of assigned work and prompt action to accomplish objectives; taking actions to achieve goals beyond what is required; being proactive

Continuous Improvement - Originating actions to improve existing conditions and processes, identifying improvement opportunities, generating ideas and implementing solutions