Senior Data Engineer

The Senior Data Engineer is responsible for designing, developing, optimizing, and supporting scalable data platforms, pipelines, and integration solutions that enable analytics, business intelligence, artificial intelligence, machine learning, and enterprise reporting initiatives across the organization.

This role partners closely with business stakeholders, data analysts, data scientists, solution architects, and technology teams to transform business requirements into reliable, secure, accessible, and scalable data solutions. The Senior Data Engineer plays a critical role in building trusted data assets, modernizing enterprise data platforms, and delivering governed data products that drive business insights and data-driven decision-making.

Beyond traditional data engineering responsibilities, this position contributes to data architecture, data modeling, governance, and platform design efforts to ensure scalable, sustainable, and high-performing data ecosystems. The Senior Data Engineer serves as a technical expert who combines hands-on development experience with technical leadership to deliver modern data solutions that generate measurable business value while supporting the organization's long-term data strategy.

This role supports modern cloud-based and hybrid data environments, ensuring high standards of performance, quality, reliability, scalability, security, and governance across enterprise data platforms.

n this role, your responsibilities will be:

• Build, develop, and optimize ETL/ELT pipelines and data integration frameworks involving structured, semi-structured, and unstructured data sources.
• Design, develop, and maintain scalable data pipelines and integration solutions using cloud and on-premises technologies.
• Build, optimize, and manage enterprise data warehouses, data lakes, and modern data platforms.
• Design and maintain conceptual, logical, and physical data models that support analytics, reporting, artificial intelligence, and data science initiatives.
• Develop reusable data products and trusted data assets that enable business intelligence, machine learning, and data-driven decision-making.
• Ensure data quality, integrity, reliability, performance, and availability across all supported data platforms.
• Implement CI/CD practices, automated testing, monitoring, and deployment frameworks for data solutions.
• Analyze and resolve complex data issues while driving continuous improvements in data processes and technologies.
• Collaborate with business stakeholders, analysts, data scientists, architects, and technology teams to translate business requirements into scalable data solutions.
• Lead data engineering initiatives from requirements gathering through deployment and ongoing support.
• Establish and maintain data governance, metadata management, data quality, and data alignment standards across the data ecosystem.
• Define and evolve enterprise data architecture standards to ensure scalability, reliability, security, and alignment with business objectives.
• Ensure data security, compliance, and adherence to enterprise standards and best practices.
• Create architecture diagrams, technical documentation, data flow documentation, and operational procedures.
• Collaborate with internal and external partners to implement and support enterprise data solutions.
• Evaluate emerging technologies and recommend opportunities to modernize and enhance the organization's data landscape.
• Partner with data scientists to enable predictive analytics, machine learning solutions, and advanced analytical applications.
• Mentor team members and provide technical leadership across data engineering initiatives, when applicable.

Who you are:

You are a strategic and results-driven professional who builds strong partnerships, communicates effectively across technical and business teams, and thrives in complex environments. You challenge the status quo, drive continuous improvement, and leverage sound judgment to deliver scalable data solutions that enable business insights and data-driven decision making. Guided by a strategic mindset, collaboration, and accountability, you consistently deliver outcomes that create value for the organization.

For this role, you will need:

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Software Engineering or a related technical field.
• Minimum of 6 years of progressively responsible experience in Data Engineering, Data Architecture, Data Warehousing, or related disciplines.
• Strong experience designing, developing, and supporting ETL/ELT pipelines and data integration frameworks.
• Hands-on experience with data ingestion, transformation, orchestration, and cloud data platform technologies such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure SQL Database, and Azure DevOps, among others..
• Strong programming skills in Python.
• Advanced expertise in SQL and relational database design.
• Strong experience designing and implementing enterprise-scale data solutions.
• Strong knowledge of dimensional modeling, star schema, and modern data modeling methodologies.
• Proven experience building and supporting data warehouses, data lakes, and modern data platforms.
• Experience delivering governed data products that support analytics, reporting, machine learning, and business decision-making.
• Experience with CI/CD implementation and DevOps practices for data solutions.
• Knowledge of data governance, metadata management, data quality, and data security best practices.
• Proven experience defining data architecture standards and designing scalable data platforms.
• Strong understanding of the relationship between data engineering, analytics, artificial intelligence, and data science ecosystems.
• Ability to lead cross-functional initiatives and influence stakeholders without direct authority.
• Experience working within Agile development methodologi