Sr. Data EngineerJoin a high-performing, tight-knit team at a fast-growing company using the Internet of Things (IoT) to transform how organizations maintain compliance, enhance safety, and reimagine operations. SmartSense by Digi and Jolt are trusted by some of the world's most recognizable brands including CVS Health, Walgreens, Walmart, McDonald's, Jack in the Box, Hartford HealthCare, and Children's Minnesota to protect their operations and the people they serve. We're looking for team-oriented change agents who want to help shape the future of IoT. Position Data Services team members are passionate about data products, engineering data flows, storage, and enabling predictive analytics. We are inspired by data products and data services and in building and delivering tools, infrastructure, frameworks that enable insights of our business increasing the value of our data to our customers. As good stewards of our data we contribute to all aspects related to the handling of data, whether from monitoring data flows, our field sensors, PII (Personally Identifiable Information), or reflecting internal processes such as our supply chain. Location: Boston, MA or Lehi, UT preferred (Hybrid) but open to remote US.In this Sr. Data Engineer role, you will contribute to strategic data engineering solutions moving data from raw to cold storage, through ETL (Extract, Transform, Load) pipelines, to data sets used to train ML (Machine Learning) models. You will collaborate with our Data Science, Business Analysts and Machine Learning Engineers producing quality data flows, transformations, and cleansing towards improved data products for the customer. You will facilitate the democratization of data for data scientists to experiment and train machine learning models and business analysts supporting the enterprise. You will have an enthusiasm and drive to deliver data products that exceed expectations, a passion for data engineering and bring an eagerness to learn. This is an exciting opportunity for an engineer ready to bring this enterprise forward on our data maturity path towards predictive analytics. Join us on our data journey.What You Will DoJoin a tightly knit team solving hard problems the right wayUnderstand the various sensors and environments critical to our customers' successKnow the data flows and technology that are currently in use to transform raw data into analytic productsBuild relationships with the awesome team members across other functional groupsLearn our code practice, work in our code base, write tests, and collaborate with us in our workflowsContribute to on-boarding processes and make recommendations to make on-boarding process betterDemonstrate your capabilities defining solutions, implementing, and delivering data products for your user stories and tasksContributing to systems and processes to implement and automate quality on data pipeline deliverablesImplement 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 usedIdentify opportunities to improve our infrastructure, operational performance, and data pipeline deliverablesEvaluate new technologies and build proof-of-concept systems to enhance Data Engineering capabilities and data productsContribute to improving the efficiency of our pipeline scripts, automation, and general data operationsDemonstrate command and accountability for the design and implementation of new featuresDevelop and support data operations and efficiencies in productionDemonstrate competencies in data modeling new and existing capabilities while progressing the maturity of our dataInfluence your peers through your excellence in delivering high quality data products and code reviewsDeliver operational data from the data platform to software and analytic teams producing aggregate metrics from real time data streamsEstablish a reputation for reliability in data contextualization and troubleshooting with the teamImprove 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 contextsTransform ETL development with optimizations for efficient storage, retention policies, access, and computation while accounting for costContributing to the strategic maturity of all our operations and delivery of product requestsDefine orchestrations of data transformations that distill information to highly valuable signals for ML modelsCollaborate with your teammates to deliver a data analytics and AI platform for advanced analytic data product developmentWithin 1 Month, you'llJoin a tightly knit team solving hard problems the right wayUnderstand the various sensors and environments critical to our customers' successLearn the data models and flows that are currently in use to transform raw data into analytic productsBuild relationships with the awesome team members across other functional groupsLearn our code practice, work in our code base, write tests, and collaborate with us in our workflowsContribute to on-boarding processes and make recommendations to make on-boarding process betterWithin 3 Months, you'llDemonstrate your capabilities defining solutions, implementing, and delivering data products for your user stories and tasksImplement data quality tests, support existing pipelines & procedures, and optimize warehouseWork closely with the product team and stakeholders to understand how our products are usedIdentify opportunities to improve our infrastructure, operational performance, and data pipeline deliverables and influence us all to be betterWithin 6 Months, you'llEvaluate new technologies and build proof-of-concept systems to enhance Data Engineering capabilities and data productsContribute to improving the efficiency of our automation and general data operationsDesign and implement new features and be accountable for their performanceDeliver high quality operational dataGenerate high quality documentation and detailed analysisArticulate conceptual, logical, and physical data models in confluenceJoin the on-call rotation for your team supporting product services and responding to incidents.Within 12 Months, you'llEstablish a reputation as a partner in data analysis and contextualization with clear articulations about our data space for targeted internal audiences.Deliver infrastructure required for optimal extraction, transformation, and data loading in predictive analytic contextsTransform ETL development with optimizations for efficient storage, retention policies, access, and computation while accounting for costContribute to the strategic maturity of our operations and delivery of product requestsKey Player in the design and delivery of the data pipelines and engineering infrastructure which support machine learning systems at scaleCollaborate with your teammates to advance our architecture in support of the predictive analytics roadmapWho You Are and What You BringBachelor'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. Desired But Not Required 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