Data Platform Engineer

PeopleSuite Talent Solutions
Indianapolis, IN, United States
1 day ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Data Analysis Microsoft Azure Batch Processing Big Data Cloud Computing Information Systems Continuous Delivery Continuous Integration Data Architecture Information Engineering Data Hub
+33 more
Data Infrastructure Data Integration Data Transformation Data Structures Data Systems Relational Databases DevOps SQL Azure Operational Data Store Performance Tuning Reliability Engineering Cloud Services Standard Sql DataOps Azure Data Lake SQL Databases Enterprise Data Management Data Processing Enterprise Software Applications Data Ingestion Database Optimization Infrastructure as Code (IaC) Data Lakes Information Technology Deployment Automation Google Cloud Functions Data Analytics Data Management Cloud Optimization Azure Synapse Analytics Multiplatform Data Pipelines Serverless Computing

Job description

Our Client is seeking a Senior Data Platform Engineer to serve as the technical authority for our Operational Data Hub within the Global Data & Analytics team. In this role, you will architect and lead the design, implementation, and optimization of enterprise-scale data ingestion, transformation, and integration solutions that power critical business operations.

As a senior technical contributor, you will own the Data Hub architecture, establish engineering standards, and drive innovation across our data platform ecosystem. You’ll work closely with Data Architects, Lead Engineers, and business stakeholders to deliver scalable, reliable, and high-performing data solutions while mentoring fellow engineers and influencing technical strategy.

This role is ideal for a hands-on data engineering leader who enjoys solving complex technical challenges, shaping platform direction, and building modern cloud-based data capabilities.

Responsibilities

Data Platform Architecture & Engineering

  • Own the architecture, design, and evolution of the Operational Data Hub and its supporting processes.
  • Design and implement scalable data ingestion, transformation, orchestration, and transmission frameworks.
  • Establish technical standards, best practices, and reusable patterns for pipeline development, monitoring, error handling, and operational excellence.
  • Architect and optimize event-driven, real-time, and batch data processing solutions.
  • Lead technical design reviews and make key architectural decisions related to integrations, processing frameworks, and platform capabilities.
  • Evaluate emerging technologies and recommend innovative solutions to enhance platform performance and scalability.

Enterprise Data & Integration

  • Partner closely with Data Architects to align platform capabilities with enterprise data models and business requirements.
  • Provide technical expertise on data structures, processing efficiency, transformation complexity, and integration strategies.
  • Design and implement robust integrations across ERP systems, APIs, and enterprise applications.
  • Build advanced data transformation and enrichment capabilities that support enterprise analytics and operational workflows.

Reliability, Governance & Optimization

  • Establish data quality, validation, testing, and monitoring frameworks to ensure trusted and reliable data.
  • Implement governance, security, compliance, and operational controls across data processing workflows.
  • Drive platform performance tuning, scalability improvements, and cloud cost optimization initiatives.
  • Lead production support efforts, including incident resolution, root cause analysis, and post-incident reviews.
  • Develop comprehensive technical documentation, architecture guides, operational runbooks, and knowledge resources.

Leadership & Mentorship

  • Serve as the go-to technical expert for Data Hub architecture and engineering practices.
  • Mentor and guide Data Platform Engineers on architecture, development standards, and operational best practices.
  • Collaborate across engineering, architecture, and business teams to drive successful delivery of strategic initiatives.
  • Influence technical direction through thought leadership, knowledge sharing, and continuous improvement.

Requirements

  • 5+ years of experience designing and delivering enterprise data platforms, data hubs, or large-scale data processing solutions.
  • Proven expertise building and owning modern data pipeline architectures, including real-time, event-driven, and batch processing patterns.
  • Deep experience with cloud-native data solutions, preferably within the Microsoft Azure ecosystem.
  • Advanced experience designing and optimizing Azure SQL Database or similar relational data platforms.
  • Strong expertise in Azure Function Apps, serverless computing, or comparable cloud-based processing frameworks.
  • Expert-level SQL skills with a demonstrated ability to optimize performance and support data modeling initiatives.
  • Experience integrating data across ERP systems, APIs, and enterprise applications.
  • Strong understanding of enterprise data architecture principles and modern data platform design.
  • Experience implementing CI/CD pipelines, Infrastructure as Code (IaC), and automated deployment practices.
  • Proven success troubleshooting complex production issues and improving platform reliability and performance.
  • Experience implementing security, governance, compliance, and operational controls within enterprise data environments.

Preferred Qualifications

  • Experience with Azure Data Lake, Azure Synapse Analytics, or similar modern data platform technologies.
  • Knowledge of DataOps, DevOps, observability, monitoring, and operational excellence practices.
  • Experience optimizing cloud infrastructure and managing data platform costs at scale.
  • Prior experience mentoring engineers and leading technical initiatives across cross-functional teams.

Education

  • Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.

Skills: Application Programming Interface (API), Architectural Services, Best Practices, Business Model, Business Operations, Cloud Computing, Computer Science, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Cost Control, Cross-Functional, Data Analysis, Data Lake, Data Management, Data Modeling, Data Processing, Data Quality, Data Structures, Database Optimization, DevOps, ERP (Enterprise Resource Planning), Ecosystems, Emerging Technology, Enterprise Applications, Enterprise Architecture, Enterprise Data Integration, Error Handling, Hubs, Identify Issues, Incident Management, Information Technology & Information Systems, Mentoring, Microsoft Windows Azure, Multiplatform/Cross-Platform, Operational Audit, Performance Tuning/Optimization, Problem Solving Skills, Process Improvement, Production Support, Relational Databases (RDBMS), Reliability Engineering, Root Cause Analysis, SQL (Structured Query Language), SQL Databases, Strategic Planning, Technical Leadership, Technical Strategy, Technical Writing, Technical/Engineering Design, Thought Leadership, Validation Testing, Workflow Analysis

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