AI Data Engineer - Senior

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.

RESPONSIBILITIES

Skills and Experience:

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.

QUALIFICATIONS

Qualifications:

• 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

Job Systems/Information Technology

Organization Cummins Inc.

Role Category Remote

Job Type Exempt - Experienced

ReqID 2420252

Relocation Package No