Senior Data Engineering Jobs (NOW HIRING)

Position Purpose:

The Sr Data Engineering Manager is responsible for defining and executing the enterprise data engineering strategy, ensuring scalable, secure, and business-aligned data platforms that enable advanced analytics, AI, and digital transformation initiatives. This role provides strategic leadership across data architecture, platform engineering, data governance, and engineering operations while building and developing high-performing teams.

As a senior leader, this position partners closely with executive leadership, product organizations, business stakeholders, enterprise architecture, cybersecurity, and analytics teams to establish a modern data ecosystem that accelerates business outcomes. The Sr Data Engineering Manager drives technology roadmaps, investment decisions, operational excellence, and organizational capability development while ensuring data platforms remain scalable, reliable, and future-ready.

Key Responsibilities:

• Enterprise Data Strategy & Roadmap: Define and execute the multi-year enterprise data engineering roadmap aligned with business strategy.
• Enterprise Data Strategy & Roadmap : Establish standards, frameworks, and governance practices for data architecture, engineering, and platform operations, particularly Snowflake and SQL Server, to enhance data infrastructure scalability and efficiency.
• Enterprise Data Strategy & Roadmap : Own data engineering budgets, cloud spend optimization, vendor relationships, and technology investment planning.
• Enterprise Data Strategy & Roadmap : Drive modernization initiatives including cloud migration, real-time analytics, AI/ML enablement, and self-service data capabilities.
• Organizational Leadership : Lead multiple engineering team members while developing succession plans and leadership pipelines. Establish engineering operating models, performance metrics, career development frameworks, and workforce planning strategies. Foster a culture of innovation, accountability, continuous learning, and operational excellence.
• Architecture Governance : Establish architectural standards for cloud data platforms, data products, integration frameworks, metadata management, and data quality. Lead architecture reviews and ensure compliance with security, governance, and regulatory requirements.
• Cross-Functional Collaboration: Partner with product managers, enterprise teams, and technical teams to standardize and govern data products across the ecosystem, ensuring alignment with organizational goals and data governance policies.
• Project and Resource Management: Oversee the allocation of team resources and financial assets to ensure successful completion of data engineering projects, aligned with strategic business objectives.
• Solution Development and Integration: Develop and integrate cutting-edge data environments with emerging technologies, streamline processes, and facilitate seamless integration with organizational systems.
• Quality Assurance and Code Optimization: Conduct rigorous unit testing and peer reviews to ensure high-quality, efficient, and scalable code, maximizing performance and minimizing risk.
• Stakeholder Engagement: Engage directly with business stakeholders to gather requirements and deliver cloud-based, customer-focused solutions that enhance user experiences and meet business needs.
• Risk and Issue Management: Identify process improvement opportunities within the data engineering function, implement risk control measures, and manage escalations to foster continuous improvement and innovation.
• Agile Process Facilitation: Manage agile ceremonies, including daily scrums, backlog grooming, sprint planning, and retrospectives, to maintain team alignment, productivity, and agile best practices.

Direct Manager/Direct Reports:

• The Sr Data Engineering Manager will report directly to the Sr Director of Data Engineering. This position includes supervisory responsibility, with a direct reporting line of data engineers and technical staff. The role necessitates strong leadership and management skills to effectively guide and support the team in achieving strategic objectives. The Sr Data Engineering Manager will be accountable for ensuring the team delivers high-quality, cloud-based data solutions aligned with business goals.

Travel Requirements:

• The Sr Data Engineering Manager in the Company is required to travel occasionally for stakeholder engagement and cross-functional collaboration to ensure alignment on strategic objectives and effective implementation of data engineering solutions.

Physical Requirements

• The Sr Data Engineering Manager will primarily work in a standard office environment, which encompasses necessary physical activities like sitting, standing, and computer use for extended periods. Effective performance in this role relies on the ability to handle regular communication through verbal and written forms. This position requires occasional movement within the office to collaborate with team members and attend meetings. It is essential for the individual to havethe visual acuity to perform tasks involving computer screens and other analytical tools. The Company is committed to providing reasonable accommodations to ensure employees with disabilities can perform essential job functions. Employees requiring accommodations are encouraged to discuss their needs with management to facilitate appropriate adjustments that enable success in the role.

Working Conditions

• The Sr Data Engineering Manager at the Company will operate within a dynamic, hybrid work environment, providing the flexibility to balance remote work with in-office collaboration as needed to drive project success and innovation. The role is set in a fast-paced, deadline-driven setting, demanding proactive engagement and composure under pressure to meet ambitious objectives. This position requires the ability to prioritize and multi-task effectively, while leading cross-functional teams in an evolving technological landscape. Successful candidates will demonstrate adaptability in coordinating with developers, product managers, and executives to achieve strategic goals and deliver state-of-the-art data engineering solutions. The role includes a focus on continuous improvement and relentless pursuit of excellence, fostering a culture of high-performance and team cohesion that is essential for advancing the company's data product roadmap.

Minimum Qualifications

• Minimum of 10 years of experience in Data Engineering or equivalent, demonstrated through work experience, academic training, military service, or education.
• At least 5 years of proven management experience, showcasing the ability to lead and develop high-performing teams.
• A minimum of 5 years of hands-on experience in data warehousing, specifically utilizing Snowflake.
• Comprehensive understanding of systems architecture and design principles to effectively develop and implement data solutions.
• Adept at building in-depth subject matter knowledge in individual data domains, with the capacity to guide and mentor development teams.
• Proficient in development languages such as Python, SQL, Scala, or Java.
• Experienced in real-time data and streaming application development, with at least 2 years of direct exposure.
• Demonstrated experience with at least one public cloud platform, such as AWS, Microsoft Azure, or Google Cloud, for a minimum of 3 years.
• Familiarity with data ecosystem tools for real-time batch data ingestion, ETL processing, and reporting.
• Background in the supply chain or distribution industry, providing valuable insights and domain-specific strategies.
• Exposure to multiple platform stacks and tools including but not limited to Databricks, Matillion, DBT, and Airflow Orchestration.
• Experience in cloud data engineering and migration processes, enhancing organizational data capabilities.
• Strong ability to collaborate with digital product managers and various stakeholders to deliver robust, cloud-based data solutions.
• Proven experience in gathering technical and business requirements and effectively communicating them to internal and external partners.
• Ability to manage and influence internal partners associated with the data technology function to achieve strategic objectives.
• Experience in identifying opportunities for data engineering process improvements and developing risk control measures.
• Proficient in managing and supporting risks encountered by the engineering team and driving continuous improvement efforts.

Preferred Qualifications

• Advanced experience in development using modern programming languages such as Python, SQL, Scala, or Java, with a minimum of 5 years leading development projects in these or similar languages.
• Demonstrated proficiency in working with real-time data processing and streaming applications, with at least 2 years of hands-on experience in this area.
• Extensive experience, over a minimum of 3 years, in leveraging public cloud services, such as AWS, Microsoft Azure, or Google Cloud, to architect and deploy scalable data solutions.
• Familiarity with supply chain or distribution industry practices, which would facilitate a deeper understanding of the SRS Distribution business model and objectives.
• Competency in handling and integrating multiple platform stacks and tools, such as Databricks, Matillion, DBT, and Airflow Orchestration, to enhance data processing workflows.
• Proven expertise in conceptualizing and designing systems architecture specifically tailored for data-centric solutions.
• Experience with data ecosystem tools, emphasizing real-time batch data ingestion, ETL processes, and effective reporting solutions.
• A strong background in cloud data engineering and a history of successful data migrations, underscoring the ability to transition legacy systems into modern cloud-based architectures.
• Prior experience in technical roles within the distribution industry, with a focus on optimizing data management processes and systems.
• Demonstrated ability to lead technical teams, with a focus on promoting best practices in data modeling and establishing governance standards across the data environment.
• Strong business acumen with proven experience in translating complex business requirements into scalable and effective technical solutions, fostering cross-functional collaboration and alignment.

Minimum Education:

• The minimum education requirement for the Sr Data Engineering Manager position is a Bachelor's degree in Computer Science, Information Technology, or a related technical field from an accredited institution.

Preferred Education:

• A Master's degree in Computer Science, Data Engineering, Information Technology, or a related technical field is highly desirable, complementing the foundational expertise required for advanced leadership in data solutions.

Minimum Years of Work Experience:

• Candidates must possess a minimum of 8 years of data engineering experience or its equivalent, which can be demonstrated through any combination of work experience, training, military service, or education. Additionally, applicants are required to have accumulated at least 3 years of management experience and 3 years in data warehousing, specifically with Snowflake.

Certifications:

• Certified Data Management Professional (CDMP) - Preferred
• AWS Certified Data Analytics Specialty - Preferred
• Google Professional Data Engineer Certification - Preferred
• Microsoft Certified: Azure Data Engineer Associate - Preferred
• Snowflake SnowPro Core Certification - Preferred

Competencies:

• Technical Expertise: Demonstrates proficiency in data engineering principles and technologies, including cloud-based platforms such as AWS, Azure, or Google Cloud. Proven track record in developing data solutions, data warehousing (e.g., Snowflake), and familiarity with multiple platform stacks and tools (e.g., Databricks, Matillion).
• Leadership and Team Management: Exhibits strong leadership capabilities by guiding and mentoring engineering teams. Manages resource allocation and oversees agile ceremonies to ensure strategic objectives and project commitments are met.
• Strategic Communication: Effectively communicates complex technical concepts to various stakeholders, including developers, executives, and product managers, ensuring alignment and collaborative solution development.
• Adaptability and Problem Solving: Demonstrates the ability to swiftly adapt to new technologies and processes. Identifies, analyses, and solves complex technical issues while recommending effective improvements to current systems.
• Business Acumen: Possesses strong business knowledge and the ability to translate organizational needs into actionable engineering plans. Engages with business stakeholders to gather requirements and drive customer-centric solutions.
• Technical Innovation and Risk Management: Leads data modeling efforts and drives cloud optimization. Oversees the integration of new technologies and processes while identifying opportunities for process improvements and managing associated risks.
• Agility and Process Enhancement: Manages agile practices within the team, promoting a culture of rapid iteration and continuous improvement. Identifies system deficiencies and implements solutions to enhance team productivity and product quality.
• Cross-functional Collaboration: Collaborates with cross-functional teams to standardize data governance and enhance product outcomes while fostering a collaborative environment for shared success in product development and delivery.

Work Location: McKinney, TX

Remote/Virtual, hybrid or in-office: Hybrid