Data Analytics Engineer

DESCRIPTION

Job Summary

HYBRID ROLE

The Data Analytics Engineer serves as the operational arm of data analytics, functioning as a power user within the analytics ecosystem. This role supports the implementation of data governance decisions, ensures high data quality, maintains documentation, and enables end users through training and guidance. The position plays a critical role in data integration, cleansing, modeling, and in delivering insights that support effective business decision-making.

Key Responsibilities

• Support data, compliance, and environment governance processes for the assigned domain.
• Facilitate an intake process to reduce rework, promote reuse, and improve efficiency of analytics solutions.
• Collaborate with cross-functional teams to integrate data from warehouses, data lakes, and other sources to build models aligned to business needs.
• Cleanse and validate data to ensure report accuracy; maintain documentation of cleansing and transformation processes.
• Support analytics projects and generate business insights through reports, dashboards, and BI tools.
• Assist in developing and enforcing standards for data collection, integration, and data management processes.
• Contribute to ingestion of key domain data into the data lake and maintain relevant metadata and data profiles.
• Help business teams locate, access, and understand available data.
• Participate in communities of practice to promote responsible analytics usage and continuous improvement.
• Coach and assist business users in developing analytics capabilities and adopting analytics tools.
• Prepare clear and concise communication materials for leaders and key stakeholders.

RESPONSIBILITIES

Core Competencies

• Collaborates: Works effectively with partners and teams to meet shared objectives.
• Communicates Effectively: Delivers clear, audience-appropriate communication across multiple channels.
• Customer Focus: Develops strong relationships and delivers customer-centric solutions.
• Interpersonal Savvy: Engages comfortably with diverse individuals and groups.
• Values Differences: Recognizes and leverages diverse perspectives.

Technical Competencies

• Data Analytics: Extracts, interprets, and communicates qualitative and quantitative data using tools such as Python (Pandas, NumPy) and SQL to produce actionable insights.
• Data Mining: Identifies patterns and relationships using exploratory techniques, including Python-based EDA, visualization libraries (Plotly/Matplotlib), and SQL queries.
• Data Modeling: Builds and tests data models, scripts, and automation aligned with business, technical, and compliance requirements.
• Data Communication & Visualization: Creates reports using Python frameworks (Plotly, Dash, Streamlit) to articulate business problems, root causes, and solutions.
• Data Literacy: Understands data constructs, sources, methods, and business applications.
• Data Profiling: Identifies data quality issues and performs extraction, mapping, and testing.
• Data Quality: Detects and corrects data flaws, supporting governance and decision-making.

Qualifications, Skills & Experience (External Candidates)

Education

• College, university, or equivalent degree in a relevant technical discipline required.
• This role may require licensing related to export control or sanctions compliance.

Experience

• Minimal relevant professional experience required.
• Exposure to data analytics, data engineering, or similar technical fields preferred

QUALIFICATIONS

Internal Candidate-Specific Qualifications & Technical Skills

Technical Skills

Python

• Proficient in Python for data analysis, statistical modeling, and automation.
• Hands-on experience with Pandas, NumPy, SciPy, Plotly.
• Ability to build UI components and dashboards using Streamlit, Dash, Tkinter, etc.
• Conduct exploratory data analysis (EDA) to uncover trends and anomalies.
• Develop scripts for data cleaning, transformation, validation, and feature engineering.
• Build automated workflows and pipelines to streamline recurring analytics tasks.

SQL & Database Management

• Strong SQL skills for querying, transforming, and analyzing relational data.
• Experience with complex joins, window functions, CTEs, aggregations, and query optimization.
• Ability to work with large, normalized datasets and reusable SQL scripts.

Statistics (Basic)

• Conduct statistical analysis and hypothesis testing.
• Apply statistical methods for forecasting, trend analysis, and predictive insights.

Collaboration & Documentation

• Work closely with business users to understand requirements.
• Provide training and support for analytics tools and processes.
• Maintain clear, structured documentation for data processes and solutions.

Skills & Experience (Internal Candidates)

• B. Tech/BE in Computer Science, IT, or related field (or equivalent education/experience).
• 1–3 years of hands-on experience with Python and SQL.
• Proficiency in Python libraries such as Pandas, NumPy, Matplotlib/Plotly.
• Basic understanding of statistical concepts and techniques.
• Strong SQL proficiency and experience with data analysis workflows.

Job Quality

Organization Cummins Inc.

Role Category Off-site Remote

Job Type Exempt - Experienced

ReqID 2422567

Relocation Package Yes

100% On-Site No