Data Engineer

Role Overview

We are seeking a highly skilled Data Engineer to design and build scalable data pipelines that ingest, transform and manage manufacturing operations data from diverse and custom source systems into AWS S3 based data platforms.

• Design, develop and maintain scalable ETLELT pipelines into AWS S3.
• Build pipelines for MES/MOM, SCADA, PLC historians and custom systems.
• Support batch and real‑time ingestion.
• Integrate heterogeneous and proprietary manufacturing systems.
• Develop connectors for APIs, OPCUA, databases and files.
• Use AWS services including S3, Glue, Lambda, Kinesis and EMR.
• Implement partitioning, lifecycle and cost optimization.
• Build analytics‑ready datasets.
• Standardize manufacturing data and time‑series datasets.
• Implement validation, monitoring and governance to ensure completeness, accuracy and security.
• Optimize for high throughput and low latency.
• Work with IT/OT teams, data scientists and architects.

• Python, PySpark, SQL.
• AWS services: S3, Glue, Lambda, Kinesis.
• Experience with ETLELT and streaming pipelines.

• MES, SCADA, OPCUA, MQTT.
• Historian systems like AVEVA PI.

510 years in data engineering

• Data pipeline reliability
• Data latency
• Data quality scores
• Cost optimization

Actual compensation within the range will be dependent upon the individual's skills, experience, performance and internal equity.

• Comprehensive Medical Plan covering Medical, Dental, Vision.
• Short Term and Long Term Disability Coverage.
• 401(k) Plan with Company match.
• Life Insurance.
• Vacation Time, Sick Leave, Paid Holidays.
• Paid Paternity and Maternity Leave.

The compensation and benefits information provided herein is accurate as of the date of this posting.

LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family‑care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.