Sr Data Engineer - Remote US, Hybrid - Lehi, UT, Mishawaka, IN or Boston, MA)

SmartSense by Digi is a fast-growing company leveraging the Internet of Things (IoT) to enhance operational compliance and safety. In the Sr. Data Engineer role, you will develop strategic data engineering solutions, collaborate with various teams, and contribute to the improvement of data products and analytics capabilities.

Responsibilities:

• Join a tightly knit team solving hard problems the right way
• Understand the various sensors and environments critical to our customers’ success
• Know the data flows and technology that are currently in use to transform raw data into analytic products
• Build relationships with the awesome team members across other functional groups
• Learn our code practice, work in our code base, write tests, and collaborate with us in our workflows
• Contribute to on-boarding processes and make recommendations to make on-boarding process better
• Demonstrate your capabilities defining solutions, implementing, and delivering data products for your user stories and tasks
• Contributing to systems and processes to implement and automate quality on data pipeline deliverables
• Implement data tests for quality and focuses on improving inefficient tooling and adopting new transformative technologies while maintaining operational continuity
• Contribute to the quality of data and the pipeline after working closely with the product team and stakeholders to understand how our products are used
• Identify opportunities to improve our infrastructure, operational performance, and data pipeline deliverables
• Evaluate new technologies and build proof-of-concept systems to enhance Data Engineering capabilities and data products
• Contribute to improving the efficiency of our pipeline scripts, automation, and general data operations
• Demonstrate command and accountability for the design and implementation of new features
• Develop and support data operations and efficiencies in production
• Demonstrate competencies in data modeling new and existing capabilities while progressing the maturity of our data
• Influence your peers through your excellence in delivering high quality data products and code reviews
• Deliver operational data from the data platform to software and analytic teams producing aggregate metrics from real time data streams
• Establish a reputation for reliability in data contextualization and troubleshooting with the team
• Improve the velocity of development of data ingestion, orchestration, fusion, transformation, and data analysis
• Deliver infrastructure required for optimal extraction, transformation, and data loading in predictive analytic contexts
• Transform ETL development with optimizations for efficient storage, retention policies, access, and computation while accounting for cost
• Contributing to the strategic maturity of all our operations and delivery of product requests
• Define orchestrations of data transformations that distill information to highly valuable signals for ML models
• Collaborate with your teammates to deliver a data analytics and AI platform for advanced analytic data product development

Requirements:

• Bachelor's or master's degree in a technical or quantitative field
• 5+ years of hands-on Data Engineering experience, delivering production-grade solutions at scale
• Expert in Snowflake, with proven ability to design, optimize, and deploy high-quality solutions for large-scale environments
• Advanced SQL and Python skills, including writing efficient, reusable, and well-documented code
• Proven experience building and maintaining ETL/data pipelines, including orchestration, monitoring, and optimization for performance and cost
• Strong knowledge of data warehousing, data lakes, and relational/non-relational databases
• Experience with managed cloud services (AWS or GCP) and implementing secure, scalable data solutions
• Experience delivering and articulating data models to support enterprise and data product needs
• Proficiency in DBT, including authoring transformations and automated tests
• Experience implementing automated testing frameworks (unit tests, integration tests, data-quality checks) for data pipelines
• Strong Git and Agile/Scrum experience, including code reviews and collaborative workflows
• Excellent communication skills to articulate complex technical concepts simply and collaborate effectively across teams
• Experience participating in design and code reviews and communicating feedback respectfully
• Must have experience authoring stories and bugs independently and in team grooming sessions
• Core technologies: SQL, Python, JavaScript, Snowflake, RESTful, Atlassian, DBT, Git, AWS
• Experience using GenAI tools (e.g., Windsurf, Claude, Copilot, Cursor) to accelerate development and improve data workflows
• Proven ability to build REST APIs using Python web frameworks such as FastAPI
• Familiarity with the Data Science lifecycle, including Machine Learning DataOps and supporting ML model training pipelines
• Hands-on experience with orchestration tools such as Airflow or Luigi for managing complex data workflows
• Knowledge of data governance practices, including handling PII and implementing secure data access paradigms
• Experience working with time-series telemetry data, including aggregation and optimization for analytics
• Snowflake SnowPro Certification is a plus; familiarity with other cloud data platforms or Lakehouse architectures is desirable
• Experience integrating with BI platforms and building data workflows for analytics and reporting
• Background in supporting production environments, including participation in on-call rotations and incident response
• Experience working with Kubernetes or other container-orchestration system
• Experience deploying data pipelines and data models to a production environment
• Experience operating and monitoring production data pipelines