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Principal Data Engineer

INFOSYS NOVA HOLDINGS LLC Detroit, MI

Detroit, MI

Today

Full time AWS Cloud Cloud Data Engineering

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Job Description

The Principal Data Engineer designs, develops, and maintains scalable data solutions for enterprise data engineering and analytics initiatives. The scope covers data engineering, data warehousing, data integration, and cloud-based platforms, with hands-on work across AWS and Snowflake.

Role Focus

In this onsite role based in Detroit, MI, you will build and optimize data pipelines, integration solutions, and analytics-ready data architectures. Responsibilities include ETL/ELT development, data modeling (including Data Vault), orchestration with dbt, and ensuring data quality and governance across complex environments.

Responsibilities

Design, develop, and optimize scalable data pipelines and data integration solutions.
Develop and maintain data architectures for enterprise data warehouses, data lakes, and analytics platforms.
Build and optimize ETL/ELT processes using modern data engineering tools and technologies.
Develop AWS-based solutions using S3, Lambda, and DynamoDB.
Design and implement data solutions within Snowflake and other cloud-based data environments.
Develop and maintain data models, including Data Vault modeling methodologies.
Write and optimize complex SQL and Python code for data processing and integration.
Use dbt to develop, transform, test, and manage data workflows.
Support data replication and integration using tools such as Qlik Replicate.
Work with enterprise data platforms including IBM InfoSphere DataStage and CP4D.
Develop and integrate APIs to support enterprise data and application needs.
Establish and maintain data quality, governance, metadata management, and data lineage processes.
Collaborate with engineering, architecture, analytics, and business teams to translate requirements into scalable data solutions.
Troubleshoot performance, data quality, and integration issues across complex data environments.
Provide technical leadership and guidance on data engineering architecture and best practices.

Required Skills and Qualifications

Strong experience in data engineering and enterprise data environments.
Hands-on experience with AWS, particularly S3, Lambda, and/or DynamoDB.
Strong experience with Snowflake and cloud data warehousing.
Advanced Python and SQL development skills.
Experience developing ETL/ELT and data integration solutions.
Experience with data warehousing and data modeling, including Data Vault.
Experience with dbt or similar modern data transformation frameworks.
Experience with data quality, governance, metadata management, and data lineage.
Strong understanding of relational and non-relational databases.
Experience with enterprise data integration platforms and tools.
Ability to work independently while providing technical leadership to other engineers.

Technologies

AWS, S3, Lambda, DynamoDB, Snowflake, Python, SQL, ETL/ELT, dbt, Qlik Replicate, IBM InfoSphere DataStage, CP4D, Data Vault, APIs.

Location and Work Arrangement

Location: Charlotte, NC / Detroit, MI
Work arrangement: Onsite
Onsite requirement: Ability to work from the client site on a regular basis

Job Type

Full-Time

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1mo ago

Principal Data Engineer - CX Analytics

Unum Group Portland, ME

Portland, ME

1mo ago Closed

$109k - $224k/yr Full time Business Analytics Cloud Operations Data

This position is no longer accepting applications (closed Sep 6, 2026).

Job Description

Unum Group is hiring a Principal Data Engineer to lead CX Analytics data engineering efforts focused on BI/reporting and advanced analytics.

Responsibilities

Partner with business teams to deliver development, construction, testing, and maintenance of data pipelines that support business needs.
Ingest and integrate large volumes of highly complex data from multiple sources, including DB2, SQL Server, Web API, and Teradata.
Apply validation, aggregation, and reconciliation techniques to build a rich data framework.
Collaborate with data scientists and business partners to understand business problems and analytics plans, then design data structures aligned to those use cases.
Establish and maintain best practices for the team’s data engineering strategy; track best practices across industries and drive innovation and efficiency.
Contribute to the evolution of enterprise data architecture, including adoption of current and emerging frameworks and tools (example: hosting data in Cloud).
Prepare results for interpretation and/or visualization and communicate potential value to influence strategic decision-making.
Support integration of solutions into existing business processes using automation techniques.
Continuously research and build expertise in current and emerging software and data engineering practices.
Provide support, training, and/or mentorship to lower-level Data Engineer peers.
Perform other related duties as assigned.

Requirements

Bachelor’s degree in a quantitative field is required.
8 years of professional experience (or equivalent relevant work experience) preferred.
Expertise in at least one object-oriented programming language: Java/Scala or Python.
DevOps best practices experience including CI/CD, process automation, and optimization.
Strong understanding of data architecture principles and infrastructure requirements across on-prem and Cloud platforms.
Ability to understand and present data in context, including how data will build toward a business solution.
Preferred: expertise writing complex SQL queries joining multiple tables and databases.
Independently explore databases/tables or other legacy data to identify best data sources for business problems.
Demonstrated ability to troubleshoot complex SQL queries with limited guidance.
Demonstrated ability to create logical data models combining data from multiple sources, including internal and external data.
Demonstrated communication skills; experience in financial services.
Leadership experience working with senior management and executive leadership; attention to detail while independently prioritizing work and managing multiple projects simultaneously.
Ability to understand and explain a problem and identify and communicate an appropriate solution.
Leader within the field, internally and externally.
Effective coach and mentor; actively engages peers and team members within areas of expertise.
Viewed as a leader in change management.
Maintains depth of technical understanding of third-party and cloud solutions.
People management: participates in determining staffing needs, including hiring and development.
Leads assigned team activities and projects to completion.
Engineering strategic and program management for the organization: coaches, mentors, and helps build team.
Proactively identifies and researches new approaches and skills needed for data science and advanced analytics.
Entrepreneurial self-starter.
Thorough, results-oriented problem-solver and lifelong learner with strong curiosity.
Deep expertise in their organization.
Demonstrated ability to conduct independent research and development of techniques that may be shared internally and externally.

Core Data Engineer Capabilities

Software Engineering: Expertise in at least one object-oriented language (Java/Scala or Python) plus DevOps best practices (CI/CD, automation, optimization).
Data Architecture and Infrastructure: Understanding of data architecture principles and related infrastructure requirements for on-prem and Cloud.
Holistic Data Preparation: Ability to frame and present data in the appropriate context for business use.
Data Extraction, Transform & Load: Complex SQL (multi-table/database joins), independent exploration of legacy data sources, troubleshooting complex SQL with limited guidance, and building logical data models from internal and external sources.
Core business capabilities: Communication skills, financial services experience, leadership exposure with senior/executive leaders, and ability to prioritize and manage multiple projects.
Leadership capabilities: Field leader (internal/external), coaching and mentoring, change management leadership, and maintained technical understanding of third-party/cloud solutions.

Technologies

Java
Scala
Python
CI/CD
SQL
DB2
SQL Server
Web API
Teradata
Cloud

Benefits

Health insurance
Vision insurance
Dental insurance
Short & Long-Term Disability
Generous PTO (including paid time to volunteer!)
Up to 9.5% 401(k) employer contribution
Mental health support
Career advancement opportunities
Student loan repayment options
Tuition reimbursement
Flexible work environments
Performance-based incentive plans
401(k) retirement plan with employer match up to 5% and an additional 4.5% contribution whether you contribute to the plan or not

General Summary

Principal Data Engineer role on the CX Analytics team within Unum’s Customer Experience Organization.
Lead design and implementation of data solutions enabling BI/reporting and advanced analytics with data that is accessible, reliable, and structured for use.
Build and maintain scalable data pipelines, optimize data models, and integrate new structured and unstructured sources across the ecosystem.
Enable analytics through automation and advance AI usage, including pipelines that incorporate unstructured data and LLM-based workflows to extract signal from sources such as raw text.
Define data engineering standards and best practices while mentoring engineers and partnering with BI Analysts and Data Scientists.
Shape how data flows through the team to ensure environments, pipelines, and datasets emphasize quality, scalability, and usability.
Campus-based role; current remote and field-based Unum employees may apply and will be considered per company policy.

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1mo ago

Principal Data Engineer - Enterprise Data & Analytics - Remote

Mayo Clinic Rochester, MN 🇺🇸 Remote

Rochester, MN

1mo ago Closed

$156k - $225k/yr Full time Analytics Data Data Engineer

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

Join Mayo Clinic as a Principal Data Engineer within Enterprise Data & Analytics, delivering enterprise-scale data architecture and engineering in a remote role.

Responsibilities

Shape enterprise data architecture and engineering roadmaps, contributing to solution design, development, optimization, and technical delivery.
Build and deploy data pipelines, integrations, and transformations to support analytics and machine learning workloads using open source languages and vendor software.
Provide advisory services across departments and leadership groups with independent judgment.
Collaborate with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data.
Perform exploratory data analyses, transform data, visualize trends, and develop and validate analytical models.
Translate qualitative and quantitative assessments into actionable insights for stakeholders.
Design, develop, review, and optimize production code and platform capabilities.
Offer technical leadership and mentorship to engineering teams.
Maintain up-to-date knowledge of Mayo Clinic's current solutions, coding languages, tools, and the Enterprise Data & Analytics technology framework.

Requirements

Bachelor's degree in a relevant field (engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative discipline) plus at least seven years of professional or research experience in data visualization, data engineering, or analytical modeling techniques.
Or an Associate's degree in a relevant field plus at least nine years of professional or research experience in data visualization, data engineering, or analytical modeling techniques.
In-depth business or practice knowledge may be considered in lieu of formal degree requirements.
Ability to manage a varied workload with multiple priorities and stay current on healthcare trends and enterprise changes.
Strong interpersonal and time-management skills with experience working on cross-functional teams.
Excellent analytical skills with the ability to identify and recommend solutions and a commitment to customer service.
Excellent verbal and written communication skills, attention to detail, and a high capacity for learning and problem resolution.
Advanced experience in SQL.
Advanced experience in scripting languages such as Python, JavaScript, PHP, C++, or Java, and API integration.
Experience in hybrid data processing methods (batch and streaming) using Apache Spark, Hive, Pig, Kafka.
Experience with big data, statistics, and machine learning.
Ability to navigate Linux and Windows operating systems.
Knowledge of workflow scheduling (Apache Airflow, Google Composer), Infrastructure as code (Kubernetes, Docker), and CI/CD (Jenkins, GitHub Actions).
Experience in DataOps/DevOps and agile methodologies.

Technologies

SQL, Python, JavaScript, PHP, C++, Java
Apache Spark, Hive, Pig, Kafka
Denodo, Tableau, Power BI, SAS, ThoughtSpot
DASH, d3, React
Snowflake, SSIS, Google BigQuery
Apache Airflow, Google Composer
Kubernetes, Docker, Jenkins, GitHub Actions
Linux, Windows
Apache Iceberg, Delta Lake, Apache Hudi
Parquet, Avro, ORC

Benefits

Medical: Multiple plan options.
Dental: Delta Dental or reimbursement account for flexible coverage.
Vision: Affordable plan with national network.
Pre-Tax Savings: HSA and FSAs for eligible expenses.
Retirement: Competitive retirement package to secure your future.

Preferred Candidate Will Possess

Expert-level proficiency in Python and SQL with extensive experience building enterprise-scale production systems.
Advanced expertise in scalable distributed computing frameworks and modern data processing platforms.
Extensive experience implementing and governing open data architectures using Apache Iceberg, Delta Lake, Apache Hudi, and related technologies.
Deep understanding of modern analytical storage formats including Parquet, Avro, and ORC.
Proven expertise in lakehouse architecture, data platform design, and large-scale data engineering practices.
Experience architecting cloud-agnostic solutions across multiple technology ecosystems.
Experience designing scalable, fault-tolerant, secure, and observable data platforms supporting analytics, AI, machine learning, and operational workloads.
Experience establishing enterprise engineering standards, architecture patterns, and modernization strategies.

Compensation Details

Salary range: USD 155,500 - 225,492 per year.
Exemption status: Exempt.
Education, experience and tenure may be considered along with internal equity when offers are extended.

Schedule and Work Details

Schedule: Full Time.
Hours per pay period: 80.
Schedule details: M-F daytime hours; 100% remote role; must reside within the United States.
Weekend schedule: As business needs dictate.
International assignment: No.

Site Description

Just as our reputation has spread beyond our Minnesota roots, our locations have grown to include campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, Mayo Clinic Health System campuses across the Midwest, and international locations.

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Mayo Clinic participates in E-Verify and may provide information from Form I-9 to confirm work authorization where required.

Recruiter

Laura Percival

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Principal Data Engineer - CX Analytics

Principal Data Engineer - Enterprise Data & Analytics - Remote

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