Senior Data Infrastructure Specialist

We are seeking a highly skilled and experienced Senior Data Engineer to join our team. The ideal candidate will be responsible for designing, developing, and deploying scalable data infrastructure to support analytics, optimization, and AI-driven use cases in a low-tech maturity environment.

This is an exciting opportunity to lead digital transformation in core manufacturing with a greenfield revolution. As a Senior Data Engineer, you will own the data architecture end-to-end, work closely with data scientists, full stack engineers, and operations teams, and be a driving force in creating a robust Industry 4.0-ready data architecture.

The successful candidate will have a strong problem-solving mindset and business acumen, with excellent communication skills to interface with plant engineers, business leaders, and technical teams alike. You will also have a self-starter attitude and ability to work with limited supervision, as well as comfortable working in ambiguous, high-stakes environments with evolving goals.

• Design and implement a scalable, secure, and future-ready data architecture from scratch.
• Lead the selection, configuration, and deployment of data lakes, warehouses (e.g., AWS Redshift, Azure Synapse), and ETL/ELT pipelines.
• Establish robust data ingestion pipelines from PLCs, DCS systems, SAP, Excel files, and third-party APIs.
• Ensure data quality, governance, lineage, and metadata management.
• Build and maintain modular, reusable ETL/ELT pipelines using Python, SQL, Apache Airflow, or equivalent.
• Set up real-time and batch processing capabilities using tools such as Kafka, Spark, or Azure Data Factory.
• Deploy and maintain scalable data storage solutions and optimize query performance.
• Work closely with Data Scientists to provision clean, structured data for ML/analytics use cases.
• Support Full Stack Engineers in delivering data-driven applications.
• Educate and onboard non-technical users and plant engineers to leverage dashboards and reporting tools.
• Translate business problems into scalable data engineering solutions.
• Guide the digital transformation roadmap and ensure alignment with plant operations and management.
• Mentor junior data engineers or analysts and define best practices for the team.

Key qualifications include:

• B.Tech/M.Tech in Computer Science, Data Engineering, or equivalent field.
• 10+ years in data engineering, with 2+ years in an industrial/operations-heavy environment (manufacturing, energy, supply chain, etc.).
• Proven experience independently architecting and deploying data platforms in greenfield or brownfield digital transformation environments.
• Hands-on expertise in:
  • Python, SQL, Spark, Pandas.
  • ETL tools: Airflow, Azure Data Factory, or equivalent.
  • Cloud platforms: Azure (preferred), AWS or GCP.
  • Databases: PostgreSQL, MS SQL Server, NoSQL (MongoDB, etc.).
  • Data lakes/warehouses: S3, Delta Lake, Snowflake, Redshift, BigQuery.
  • Monitoring and Logging: Prometheus, Grafana, ELK, etc.

Good to have:

• Experience working with low-maturity data environments.
• Familiarity with manual logs, Excel-based systems, or legacy SAP setups.
• Exposure to OT systems (PLC, SCADA, DCS) and IoT device integration.
• Knowledge of data mesh, data contracts, or microservice-based data flows.
• Experience with CI/CD pipelines for data applications (GitHub Actions, Azure DevOps).

Skills:

• Strong problem-solving mindset and business acumen.
• Self-starter attitude and ability to work with limited supervision.
• Excellent communication skills.
• Comfortable working in ambiguous, high-stakes environments with evolving goals.

Why Join Us:

• Opportunity to lead digital transformation in core manufacturing with a greenfield revolution.
• Ownership of data systems across the entire value chain.
• Collaborative, impact-driven work environment with high visibility to leadership.
• Be a key architect in building a lighthouse-ready Industry 4.0 digital stack.