Sr Data Engineer; Hybrid - Boston, MA

Overview

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. Smart Sense 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 Health Care, 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.

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
• 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,…