DESCRIPTION

Although the role category specified in the GPP is Remote, the requirement is for Hybrid. Key Responsibilities:

• Implement and automate deployment of distributed systems for ingesting and transforming data from various sources (relational, event-based, unstructured).

• Continuously monitor and troubleshoot data quality and integrity issues.

• Implement data governance processes and methods for managing metadata, access, and retention for internal and external users.

• Develop reliable, efficient, scalable, and quality data pipelines with monitoring and alert mechanisms using ETL/ELT tools or scripting languages.

• Develop physical data models and implement data storage architectures as per design guidelines.

• Analyze complex data elements and systems, data flow, dependencies, and relationships to contribute to conceptual, physical, and logical data models.

• Participate in testing and troubleshooting of data pipelines.

• Develop and operate large-scale data storage and processing solutions using distributed and cloud-based platforms (e.g., Data Lakes, Hadoop, Hbase, Cassandra, MongoDB, Accumulo, DynamoDB).

• Use agile development technologies, such as DevOps, Scrum, Kanban, and continuous improvement cycles, for data-driven applications.

RESPONSIBILITIES

Qualifications:

• College, university, or equivalent degree in a relevant technical discipline, or relevant equivalent experience required.

• This position may require licensing for compliance with export controls or sanctions regulations.

Competencies:

• System Requirements Engineering: Uses appropriate methods and tools to translate stakeholder needs into verifiable requirements.

• Collaborates: Building partnerships and working collaboratively with others to meet shared objectives.

• Communicates effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.

• Customer focus: Building strong customer relationships and delivering customer-centric solutions.

• Decision quality: Making good and timely decisions that keep the organization moving forward.

• Data Extraction: Performs ETL activities from various sources and transforms them for consumption by downstream applications and users.

• Programming: Creates, writes, and tests computer code, test scripts, and build scripts using industry standards and tools.

• Quality Assurance Metrics: Applies measurement science to assess whether a solution meets its intended outcomes.

• Solution Documentation: Documents information and solutions based on knowledge gained during product development activities.

• Solution Validation Testing: Validates configuration item changes or solutions using defined best practices.

• Data Quality: Identifies, understands, and corrects flaws in data to support effective information governance.

• Problem Solving: Solves problems using systematic analysis processes and industry-standard methodologies.

• Values differences: Recognizing the value that different perspectives and cultures bring to an organization.

QUALIFICATIONS

Knowledge/Skills:

Must-Have:

• 3-5 years of experience in data engineering with a strong background in Azure Databricks and Scala/Python.

• Hands-on experience with Spark (Scala/PySpark) and SQL.

• Experience with SPARK Streaming, SPARK Internals, and Query Optimization.

• Proficiency in Azure Cloud Services.

• Agile Development experience.

• Unit Testing of ETL.

• Experience creating ETL pipelines with ML model integration.

• Knowledge of Big Data storage strategies (optimization and performance).

• Critical problem-solving skills.

• Basic understanding of Data Models (SQL/NoSQL) including Delta Lake or Lakehouse.

• Quick learner.

Nice-to-Have:

• Understanding of the ML lifecycle.

• Exposure to Big Data open-source technologies.

• Experience with SPARK, Scala/Java, Map-Reduce, Hive, HBase, and Kafka.

• SQL query language proficiency.

• Experience with clustered compute cloud-based implementations.

• Familiarity with developing applications requiring large file movement for a cloud-based environment.

• Exposure to Agile software development.

• Experience building analytical solutions.

• Exposure to IoT technology.

Experience:

• Relevant experience preferred, such as working in temporary student employment, internships, co-ops, or other extracurricular team activities.

• Knowledge of the latest technologies in data engineering is highly preferred, including:

• Exposure to Big Data open source

• SPARK, Scala/Java, Map-Reduce, Hive, Hbase, and Kafka or equivalent college coursework

• SQL query language

• Clustered compute cloud-based implementation experience

• Familiarity with developing applications requiring large file movement for a cloud-based environment

• Exposure to Agile software development

• Exposure to building analytical solutions

• Exposure to IoT technology

Work Schedule:

Most of the work will be with stakeholders in the US, with an overlap of 2-3 hours during EST hours on a need basis.

Job Systems/Information Technology

Organization Cummins Inc.

Role Category Remote

Job Type Exempt - Experienced

ReqID 2410604

Relocation Package No