Technical Lead - Data Engineer

Technical Lead - Data Engineer

Join the Tech Core of a Fortune 100 Giant!

Be part of a ~$70 billion innovator where your work drives real business impact. Our client's Technology team puts customers at the heart of everything and so do we when it comes to our people. If you're passionate about cutting-edge technology and making a difference at scale, this is where you belong.

Additional Qualifications:

AWS | Snowflake | Data Platform Engineering

This role strengthens Nationwides enterprise data engineering capabilities by providing hands-on technical leadership. The position is responsible for designing, building, and supporting scalable, secure, and production-ready data solutions that enable analytics, operational reporting, and emerging AI initiatives.

The Consultant, Data Engineer | Technical Lead will partner closely with product, architecture, infrastructure, governance, and run teams to deliver modern cloud-native data products while driving engineering standards, operational reliability, and DataOps best practices.

Key Responsibilities

• Lead the design, development, and support of scalable batch and streaming data pipelines and lakehouse solutions.
• Provide hands-on expertise with AWS, Snowflake, Delta Lake, and related cloud data technologies.
• Establish and enforce standards for coding, CI/CD, Infrastructure as Code, testing, monitoring, and observability.
• Support production operations, incident resolution, and platform reliability initiatives.
• Partner with cross-functional teams to deliver secure, cost-effective, and high-quality data solutions.
• Mentor engineers through technical guidance, design reviews, troubleshooting, and best practices.

Preferred Qualifications

• Strong experience delivering enterprise-scale cloud data engineering solutions in production environments.
• Deep hands-on experience with AWS, Snowflake, Python, and modern data platform technologies.
• Experience implementing DataOps, CI/CD, and automated testing practices.
• Exposure to Investments data, including portfolios, securities, market data, or performance reporting, is a plus.
• Experience with Aladdin Studio is a plus
• Experience working within large, highly governed enterprise environments preferred.

Job Description Summary

Our Clients industry leading workforce is passionate about creating data solutions that are secure, reliable and efficient in support of our mission to provide extraordinary care. Our Client embraces an agile work environment and collaborative culture through the understanding of business processes, relationship entities and requirements using data analysis, quality, visualization, governance, engineering, robotic process automation, and machine learning to produce targeted data solutions. If you have the drive and desire to be part of a future forward data enabled culture, we want to hear from you.

As a Data Engineer youll be responsible for acquiring, curating, and publishing data for analytical or operational uses. Data should be in a ready-to-use form that creates a single version of the truth across all data consumers, including business users, data scientists, and Technology. Ready-to-use data can be for both real time and batch data processes and may include unstructured data. Successful data engineers have the skills typically required for the full lifecycle software engineering development from translating requirements into design, development, testing, deployment, and production maintenance tasks. Youll have the opportunity to work with various technologies from big data, relational and SQL databases, unstructured data technology, and programming languages.

Job Description

Key Responsibilities:

• Consults on complex data product projects by analyzing moderate to complex end to end data product requirements and existing business processes to lead in the design, development and implementation of data products.
• Responsible for producing data building blocks, data models, and data flows for varying client demands such as dimensional data, standard and ad hoc reporting, data feeds, dashboard reporting, and data science research & exploration.
• Translates business data stories into a technical story breakdown structure and work estimate so value and fit for a schedule or sprint.
• Responsible for applying secure software and systems engineering practices throughout the delivery lifecycle to ensure our data and technology solutions are protected from threats and vulnerabilities.
• Creates business user access methods to structured and unstructured data by such techniques as mapping data to a common data model, NLP, transforming data as necessary to satisfy business rules, AI, statistical computations and validation of data content.
• Builds data cleansing, imputation, and common data meaning and standardization routines from source systems by understanding business and source system data practices and by using data profiling and source data change monitoring, extraction, ingestion and curation data flows.
• Facilitates medium to large-scale data using cloud technologies Azure and AWS (i.e. Redshift, S3, EC2, Data-pipeline and other big data technologies).
• Collaborates with enterprise DevSecOps team and other internal organizations on CI/CD best practices experience using JIRA, Jenkins, Confluence etc.
• Implements production processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Develops and maintains scalable data pipelines for both streaming and batch requirements and builds out new API integrations to support continuing increases in data volume and complexity.
• Writes and performs data unit/integration tests for data quality with input from a business requirements/story, creates and executes testing data and scripts to validate that quality and completeness criteria are satisfied. Can create automated testing programs and data that are re-usable for future code changes.
• Practices code management and integration with engineering Git principle and practice repositories.
• Participates as an expert and learner in team tasks for data analysis, architecture, application design, coding, and testing practices.
• May perform other responsibilities as assigned.

Qualifications & Experience:

• Education: BE / BTech in CS or Engineering / Management Information Systems, Business Statistics or Maths.

Experience:

• 5- 8 years of relevant experience with data quality rules, data management organization/standards and practices.
• Solid experience with software development on large and/or concurrent projects.
• Experience in data warehousing, statistical analysis, data models, and queries.
• One to three years experience with developing compelling stories and distinctive visualizations.

Technical Skills:

• Amazon Web Services
• Data Engineering
• Data Management
• Data Pipelines
• Data Quality
• Extract Transform Load (ETL)
• Programming Skills
• Business Acumen

Soft Skills & Attributes:

• Data application and practice knowledge
• Strong communication skills
• Ability to influence, negotiate, and set priorities
• Mentoring and coaching abilities to guide associates
• Identifying and removing blockers to progress
• Ability to work in agile and global environments
• Insurance/financial services industry knowledge a plus
• Other criteria, including leadership skills, competencies and experiences may take precedence

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