ApplyDescription
Management Controls Inc. (MCi) is excited to welcome a Data Engineering Manager to join our dynamic team in Houston, TX. The ideal candidate will have prior experience managing Data Engineering teams with technical expertise and architecture design skills, capable of bridging technical concepts to non-technical stakeholders and fostering cross-functional relationships. This role will focus on leading and transforming our data foundation, managing Data Engineers while also rolling up their sleeves to design and implement cutting-edge data solutions.
Our environment is built primarily on Azure cloud services, and we’re looking for a leader who can drive modern best practices and future-proof our data capabilities for advanced analytics, Big Data reporting, AI, and ML initiatives.The business is privately held with 30 years of experience, services most of the Fortune 100, and is experiencing exponential growth, which will last into the next decade. In addition to normal tech company benefits like performance bonuses, flexible PTO, stocked kitchens, and an in-house gym, MCi also offers 100% paid healthcare.
We believe in innovation, teamwork, and continuous learning to stay at the forefront of technology advancements. At MCi, we foster a culture of integrity, accountability, and quality, where every team member plays a vital role in transforming how the world’s largest producers manage contractor data and spend. The ideal candidate thrives in this dynamic, collaborative environment and brings strong communication skills, critical thinking, and a proactive mindset to technically complex challenges. With a passion for operational excellence and continuous improvement, this individual builds trusted, cross-functional relationships and communicates fearlessly to contribute to a culture that values owner mentality and client value creation. At MCi, adaptability and approachability are key to solving business problems and creating value for our clients through our industry-leading platform, myTrack.
Duties and Responsibilities
- Manage, mentor, and grow a small but dedicated Data Engineering team directly integrated into the Data Science Team and larger Technology group. Lead by example, offering guidance, direction, and professional development for the Data Engineering team. Maintain effective project management practices, ensuring timely and high-quality data deliverables.
- Build and maintain a near real-time, cost-efficient, and scalable data lake that uses best-in-class architecture and adheres to modern data design principles. Design and develop data warehouses on top of the data lake to support reporting, AI agents, ML models, and well-defined schema needs.
- Design scalable data architectures using Azure tools (SQL, Data Factory, Synapse, Microsoft Fabric) and emerging technologies (Spark, Databricks). Strategize and implement near real-time data flows in Azure. Explore real-time or event-driven pipelines using streaming technologies (e.g., Kafka, Fabric Mirroring) to meet near real-time business needs.
- Own the end-to-end responsibility for the data infrastructure, from ingestion to transformation to consumption. Implement best practices for data governance, privacy, and compliance (GDPR, HIPAA, etc. as applicable). Oversee secure data access controls, encryption, and auditing procedures to protect sensitive information.
- Ensure reliability, proper organization, high data quality, documentation, and the platform’s futureproofing. Establish and maintain clear, accessible documentation for datasets, ETL processes, and system architecture. Develop a metadata management strategy or data catalog for discoverability and self-service analytics.
- Define and track KPIs such as data pipeline uptime, data freshness, cost optimization, and performance metrics. Use analytics and monitoring tools to continuously refine data workflows and architecture.
- Provide hands-on development work in SQL, Python, ETL/ELT orchestration, and more.
- Collaborate with cross-functional teams to deliver data solutions for various product features, analytics, and operational requirements. Collaborate with analytics, AI/ML, and product development teams to ensure data alignment with business goals. Lay the groundwork for our rapidly expanding AI/ML capabilities and enterprise-scale data analysis.
- Foster a culture of continuous learning and innovation within the Data Engineering team. Encourage knowledge sharing, collaboration, and professional development.
Requirements
- 5+ years managing Data or Software Engineering teams, including strategic planning and individual development.
- Expert-level SQL and high-level Python skills for complex data transformations and analytics.
- In-depth knowledge of Azure data services (SQL Server, Azure SQL, Data Factory, Synapse, Microsoft Fabric, Power BI) with a strong interest in Spark, Databricks, Power Automate/App
- Proven ability to design scalable schemas, robust data pipelines, and effective storage strategies that align with best practices; DevOps or MLOps experience setting up continuous integration/delivery for data pipelines and ML models.
- Strong background in ensuring data reliability, quality, and future-proofing strategies.
- Familiarity with modern data lake and data warehouse architectures, ETL orchestration, and real-time data ingestion.
- Strong project management skills to handle multiple priorities and deadlines.
- Capability to bridge technical concepts to non-technical stakeholders.
- Proficiency in negotiation, conflict resolution, and fostering cross-functional relationships.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Industry certifications such as Microsoft Certified: Azure Data Engineer Associate.
- Data Streaming Tools (e.g., Kafka, Fabric Mirroring) for event-driven architectures.
- Experience with data governance and compliance frameworks, including security best practices.
