Sr Data Engineer (Hybrid - Boston, MA)

Join 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.

What We Offer

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.

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

Within 3 Months, you'll

Demonstrate your capabilities defining solutions, implementing, and delivering data products for your user stories and tasks

Implement data quality tests, support existing pipelines & procedures, and optimize warehouse

Work 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 and influence us all to be better

Within 6 Months, you'll

Evaluate new technologies and build proof-of-concept systems to enhance Data Engineering capabilities and data products

Contribute to improving the efficiency of our automation and general data operations

Design and implement new features and be accountable for their performance

Deliver high quality operational data

Generate high quality documentation and detailed analysis

Articulate conceptual, logical, and physical data models in confluence

Join the on-call rotation for your team supporting product services and responding to incidents

Within 12 Months, you'll

Establish 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 contexts

Transform ETL development with optimizations for efficient storage, retention policies, access, and computation while accounting for cost

Contribute to the strategic maturity of our operations and delivery of product requests

Key Player in the design and delivery of the data pipelines and engineering infrastructure which support machine learning systems at scale

Collaborate with your teammates to advance our architecture in support of the predictive analytics roadmap

Who You Are and What You Bring

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

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 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.

*Please note that we are unable to provide visa sponsorship for this position. This includes, but is not limited to, work visas, employment-based visas, or residency sponsorship. Candidates must have valid work authorization in the United States at the time of application. Visa applications of any kind will not be considered.

Digi International offers a distinctive Total Rewards package including a short-term incentive program, new hire stock award, paid parental leave, open (uncapped) PTO, and hybrid work environment in addition to our competitive medical, health & wellbeing and compensation offerings.

The anticipated base pay range for this position is $95,000 - $149,000. Pay ranges are determined by role, job level and primary job location. The range displayed reflects the reasonable range we anticipate paying for this position and reflects the cost of labor within several U.S. geographic markets. The specific salary offered within the range will depend on various factors including, but not limited to the candidate's relevant and prior experience, education, skills, and primary work location. It is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each position. Pay ranges are typically reviewed and updated annually.

At Digi, we embrace diversity and inclusion among our teammates. It is critical to our success as a global company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. We are committed to providing an environment of respect where equal employment opportunities are available to all applicants and teammates.