AI Data Engineer

As a Senior AI Data Engineer at Cummins, you will lead the design, development, and maintenance of scalable data and analytics platforms. You will enable efficient processing, storage, and accessibility of data for analysts, data scientists, and business stakeholders. This role involves working on multiple product teams, collaborating with IT experts and subject-matter specialists, and delivering advanced analytics and AI solutions. You will also mentor junior team members and drive automation and optimization across data engineering processes.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and integration solutions for structured, semi-structured, and unstructured data.
• Build and optimize distributed systems for data ingestion, transformation, and storage from diverse sources (relational, event-based, unstructured).
• Implement frameworks to monitor, troubleshoot, and ensure data quality and integrity.
• Design and implement physical data models, indexing, and database structures to optimize performance.
• Develop and operate large-scale data storage and processing solutions using cloud-based and distributed platforms (Data Lakes, Hadoop, HBase, Cassandra, MongoDB, DynamoDB, etc.).
• Apply AI/ML concepts to support advanced analytics workflows, including regression, clustering, and time-series analysis.
• Integrate platforms such as Palantir, Snowflake, and graph databases (Neo4j, TigerGraph) into data pipelines.
• Establish data governance processes, metadata management, cataloging, and access controls.
• Automate repetitive data integration and preparation tasks to improve productivity and minimize errors.
• Collaborate with business and IT stakeholders to understand requirements, plan solutions, and deliver analytics products.
• Mentor and coach junior team members, promoting best practices in data engineering and analytics.
• Stay current with AI and data engineering trends, recommending improvements to systems and workflows.

Technical Skills (Required):

• Strong expertise in Python, SQL, and Spark (PySpark preferred).
• Experience with ETL/ELT technologies and managing large-scale datasets.
• Familiarity with Big Data frameworks and cloud-based clustered compute environments.
• Exposure to graph data modeling, graph databases (Neo4j, TigerGraph), and Palantir Ontology (preferred).
• Knowledge of AI/ML workflows, model deployment, and advanced analytics techniques.
• Experience with data governance, cataloging tools (Azure Purview, Alation), and metadata management.
• Familiarity with IoT data processing and integration is a plus.
• Strong problem-solving, system design, and programming skills.

Core Competencies:

• System Requirements Engineering – translating business needs into verifiable requirements.
• Collaboration – working effectively across teams to meet shared objectives.
• Communication – delivering technical information clearly to diverse audiences.
• Customer Focus – delivering solutions aligned with customer needs.
• Decision Making – making timely and effective technical decisions.
• Data Extraction & Quality – performing ETL/ELT tasks and ensuring data accuracy.
• Solution Documentation & Validation – creating documentation and validating solutions against requirements.
• Problem Solving – applying systematic methodologies to identify root causes and implement solutions.
• Valuing Differences – fostering an inclusive environment by recognizing diverse perspectives.

Nice to Have:

• Hands-on experience with cloud-based large file movement and distributed processing.
• Familiarity with emerging AI and Big Data technologies and frameworks.
• Proactive, self-starter mindset with strong verbal and written communication skills.

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a relevant technical discipline, or equivalent experience.
• 5–8 years of experience in data engineering, analytics, or AI/ML-related roles.
• Licensing or compliance may be required for export control or sanctions regulations.

Work Timings - 12 PM to 9 PM