Principal Data Engineer

Overview:

As a Principal Data Engineer, you will be responsible for leading the design, development, and implementation of advanced data solutions that support our enterprise-wide data strategy. This role involves driving the architecture, development, and optimization of a scalable, secure master data platform that powers advanced analytics and data-driven decision-making across the organization. The successful candidate will be instrumental in shaping the master data ecosystem, providing thought leadership, and mentoring a team of skilled data engineers.

Responsibilities

Lead the design and development of the master data platform, ensuring it meets current and future business needs. Architect data models, storage, and processing solutions that balance performance, scalability, and maintainability. Perform hands-on development work on data analysis, data provisioning, data modeling, performance tuning, and optimization. Lead the design and development of Account Master, Contact master , Products Master, Parts Master and other similar entities . Integrating these entities with upstream and downstream business systems . Design and Development in TAMR and Stibo . Api and Microservices Design and Development Perform design and development in technologies like Fivetran, Snowflake, DBT, Python, SQL, Kubernetes, Kafka and utilize cloud technologies like Azure, AWS, and GCP. Experience working with large scale structured / semi-structured / unstructured data efficiently by designing, building and maintaining robust data processing frameworks for enabling actionable insights and analytics. Define and enforce best practices for data engineering, including coding standards, source control, and CI/CD processes to minimize technical debt and ensure high-quality code deployments. Create dashboards using enterprise tools such as Tableau and PowerBI. Experience in vector, graph and NoSQL databases for complex data use-cases. Ensure the reliability, performance, and security of data platforms and solutions. Provide technical guidance and support to team members, fostering a culture of collaboration, innovation, and continuous improvement. Work closely with business unit leaders, data scientists, and analysts to understand their requirements and translate them into robust technical solutions on the Enterprise Data Platform. Implement data quality and data governance practices, ensuring data security, compliance, and quality controls, especially when handling sensitive or high-risk data. Scope key business challenges, identify the right data, and provide direction to data analysts, product managers, data scientists, and data engineers. Drive innovation by creating new frameworks, standards, prototypes, and automation projects. Stay current with emerging trends and technologies in data engineering and analytics, driving the adoption of new tools and technologies.

Qualifications:

Bachelor s or master s degree in computer science, Engineering, or a related field. 15+ years of experience in data engineering, with a focus on designing and implementing large-scale master data solutions. Proven experience in a lead role, capable of driving projects and collaborating with cross-functional teams. Strong proficiency in SQL, Python, containerization (Kubernetes), and cloud technologies like Snowflake, DBT, Dagster, etc. Experience designing, building and maintaining frameworks to handle large data volumes, streaming data use-cases using technologies like Kafka, to handle IOT / sensor/edge device data. Experience building on at least one of the cloud technologies (AWS, GCP, Azure). Deep understanding of enterprise data management and master data concepts . Experience working on Master Data Platforms like Semarchy , Profisee, Tamr , Stibo , Informatica . Outstanding communication and interpersonal skills, with the ability to engage effectively with technical and non-technical stakeholders. Strong problem-solving skills and a proactive approach to identifying and addressing challenges. Strong Knowledge of data governance, security, and compliance best practices.

Additional Qualifications (good to have):

Experience in the manufacturing industry or a similar domain. Familiarity with handling IOT / edge device data. Certifications in cloud platforms or data engineering.