Senior Data Engineer

Inmar Intelligence-posted 11 days ago

Full-time • Mid Level

Chicago, NC

1,001-5,000 employees

Resume

Match Score

Upload and Match ResumeTrack Jobs with Teal

As a Senior Data Engineer, you will play a critical role in shaping the architecture, implementation, and reliability of our cloud-native data platforms. You’ll be responsible for designing and developing scalable data solutions that support analytics, automation, and business operations across Inmar. You will work with a modern tech stack—including BigQuery, Airflow, Python, and Pub/Sub—within a Google Cloud Platform (GCP) environment, building pipelines that are secure, cost-effective, and observable. This role is ideal for someone who thrives on solving complex data challenges, mentoring junior engineers, and delivering high-impact, production-grade solutions, while collaborating cross-functionally across teams. PRIMARY ACCOUNTABILITIES: Technical (100%)

Design, build, and optimize scalable, secure, and observable data pipelines using tools like BigQuery, Dataflow, Cloud Functions, Pub/Sub, and Airflow (Composer).
Translate technical concepts into clear, actionable plans for technical and non-technical stakeholders.
Conduct data profiling and source system analysis to design reliable ingestion and transformation processes.
Build reusable, automated frameworks that support batch and streaming workflows, while continuously evaluating new tools and patterns to improve performance, reliability, and cost.
Ensure data solutions align with enterprise standards, security policies, and compliance requirements (e.g., HIPAA, CCPA).
Design and maintain data models that support OLTP, OLAP, and ML use cases.
Implement and maintain metadata management, data lineage, and impact analysis practices.
Own production issues end-to-end, including root cause analysis (RCA) and resolution with preventative improvements.
Collaborate in Agile environments—contributing to sprint planning, backlog refinement, and iterative delivery.
Provide mentorship and technical guidance to junior engineers through code reviews, knowledge sharing, and design discussions.

B.S. in Computer Science, Information Systems, or related field required, or 8+ years equivalent experience in data engineering.
Proven experience designing, building, and optimizing cloud-native, scalable, cost-efficient data pipelines and architectures, particularly on Google Cloud Platform (preferred); familiarity with AWS or Azure is a plus.
Advanced skills in Python and SQL, familiarity with dbt, Airflow, Terraform, CI/CD pipelines.
Experience with batch and streaming technologies such as Kafka, Spark, Dataflow, and Pub/Sub.
Expertise with GCP-native tools such as BigQuery, Cloud Functions, Cloud Workflows, GCS, and Datastream.
Skilled at balancing performance, reliability, and cost.
Demonstrated ability to implement automated monitoring, alerting, and data quality checks for production-grade data pipelines.
Experience with relational and NoSQL databases, such as Postgres, SQL Server and Cassandra.
Practical knowledge of data modeling and design for OLTP, OLAP, and real-time systems to support analytics, operations, and ML use cases.
Understanding of data governance practices, including lineage, metadata, access controls, and privacy compliance (e.g., HIPAA, CCPA, etc.).
Comfortable working in Agile/Scrum environments, contributing to iterative delivery, sprint planning, and technical scoping.
Proven ability to work cross-functionally with data analysts, product managers, privacy, security, and business teams to deliver trusted, actionable data products.
Strong problem-solving skills with experience in root cause analysis, writing postmortems, and driving incident resolution and continuous improvement in data platforms.
Integrity: Builds trust by taking ownership of actions, following through on commitments, and communicating with transparency.
Technical Mentorship: Supports the growth of junior engineers by sharing knowledge, providing guidance on design and implementation, and fostering a collaborative, learning-focused environment.
Team Collaboration: Works cross-functionally to align data engineering solutions with business and technical goals. Builds strong partnerships across product, data governance, and analytics teams.
Adaptability: Embraces change and innovation with a growth mindset. Adjusts approach as priorities and technologies evolve.
Innovation: Identifies and drives opportunities to improve tools, processes, or architecture through new technologies and creative problem-solving.
Curiosity: Actively seeks to understand new data domains, technologies, and stakeholder needs. Continuously develops personal and team knowledge.
Analytical Thinking: Breaks down complex systems and problems into manageable components. Makes decisions based on data and structured reasoning.
Problem Solving: Investigates and resolves complex technical issues efficiently and thoughtfully, balancing long-term and short-term solutions.

Familiarity with AI/ML workflows, including feature engineering, model training, and real-time inference; experience with Vertex AI or similar platforms is a plus.
Exposure to enterprise SaaS and ERP integrations (e.g., Oracle Cloud ERP, Salesforce, Workday, Ironclad, Replicon) and partnerships with external data vendors.

Medical, Dental, and Vision insurance
Basic and Supplemental Life Insurance options
401(k) retirement plans with company match
Health Spending Accounts (HSA/FSA)
Flexible time off and 11 paid holidays
Family-building benefits, including Maternity, Adoption, and Parental Leave
Tuition Reimbursement and certification support, reflecting our commitment to lifelong learning
Wellness and Mental Health counseling services
Concierge and work/life support resources
Adoption Assistance Reimbursement
Perks and discount programs

Track Jobs with Teal

Job Search Resources

•

AI Resume Builder

•

Senior Data Engineer Resume Examples

•

Senior Data Engineer Cover Letter Examples

Senior Data Engineer

Job Search Resources

Tools

Career Hubs

Guides

Company