{"schemaVersion":"jobsearcher.job.v1","id":"33a71de45b40f67790d428fe","url":"https://jobsearcher.com/jobs/33a71de45b40f67790d428fe","canonicalUrl":"https://jobsearcher.com/jobs/33a71de45b40f67790d428fe","title":"Data Engineer","description":"Search\r\njobs\r\n1,155\r\nExplore\r\ncompanies\r\n52\r\nJoin talent network\r\nTalent\r\nData Engineer\r\nSeurat Technologies\r\nSoftware Engineering, Data Science\r\nWilmington, MA, USA\r\nUSD 130k-165k / year + Equity\r\nPosted on Jun 22, 2026\r\nAbout Seurat\r\nSeurat is transforming manufacturing for people and our planet by delivering a scalable additive manufacturing solution to fundamentally change how products are made. Seurat's proprietary Area Printing process, developed at Lawrence Livermore National Labs (LLNL), allows metal components to be manufactured at price points and quality levels that compete directly with conventional manufacturing techniques, enabling the reshoring of supply chains and promoting the decarbonization of industry. Seurat has raised over $180M and is backed by leading venture partners like Capricorn, NVentures (NVIDIA), True Ventures, General Motors Ventures, Denso, Porsche SE, SIP global partners, Honda, Xerox Ventures/Myriad Venture Partners, Cubit Capital, Siemens Energy, and Maniv Mobility.\r\nPosition Overview\r\nSeurat is looking for an experienced Data Engineer to own and expand the upstream data foundation behind our process engineering work. The role covers ingestion, cleaning, organization, governance, and access. You will design and operate the pipelines and storage that turn raw output from numerous materials studies, machine qualification trials, application development runs, and customer builds into reliable, well-organized data that engineers, scientists, and downstream analysis or AI/ML systems can rely on.\r\nThis is a platform role. The most common day-to-day work is making our process engineers, data analysts, and ML practitioners more productive by giving them dependable data and good ways to get at it. The role is not focused on analysis or model development, although you will work closely with the people who do that work.\r\nKey Responsibilities\r\nData ingestion and integration\r\nBuild and operate the pipelines that pull in high-volume process data from Seurat's print systems and adjacent equipment.\r\nIntegrate data from heterogeneous sources, including telemetry streams, in-situ process monitoring (optical, thermal, imaging), build job metadata, powder lot and material records, and post-build inspection such as metrology, microscopy, and mechanical tests.\r\nEfficiently store and retrieve large binary artifacts such as images, layer-wise scans, and sensor traces, alongside more structured data.\r\nData cleaning and normalization\r\nAdd validation, deduplication, and normalization so that downstream consumers do not have to keep rediscovering the same data quality issues.\r\nDefine and maintain schemas across data sources whose formats change as the hardware and process evolve.\r\nWork with hardware, process, and software engineers to address data quality problems at the source rather than only in flight.\r\nData lake and storage\r\nDesign and run Seurat's data lakehouse, including partitioning strategies, file formats such as Parquet, HDF5, and Zarr, schema enforcement, retention, and cost management.\r\nBuild catalog and lineage tooling so that engineers can find and understand the data they need without relying on tribal knowledge.\r\nPick the right storage tier for each workload across object storage, time-series, relational, and search systems.\r\nData access and tooling\r\nProvide well-documented access patterns, including query interfaces, APIs, and notebooks, so that process engineers, analysts, and ML practitioners can be productive without becoming infrastructure experts themselves.\r\nManage access control, governance, and auditing sensitive or proprietary data.\r\nBuild internal tooling that lowers the cost of common data tasks, including extraction, joining, exploration, and sharing.\r\nReliability and operations\r\nInstrument pipelines for observability and respond to failures and data quality regressions.\r\nEstablish testing patterns appropriate to data systems, including contract tests, data quality checks, lineage verification, and backfills.\r\nKey Goals and Expected Outcomes\r\nA reliable, well-organized process data foundation. Process and inspection data is ingested, cleaned, and made accessible without ad-hoc effort from downstream consumers.\r\nMeasurable improvements in data quality. Freshness, completeness, and correctness across the most important datasets are tracked and trending in the right direction.\r\nSelf-service. Process engineers, analysts, and AI/ML engineers can answer their own data questions with confidence in the underlying data.\r\nA scalable platform. The data foundation grows with Seurat's print fleet, sensor coverage, and product diversity without requiring proportional headcount.\r\nQualifications\r\nBachelor's degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.\r\n3+ years of professional experience as a Data Engineer or in a closely related role.\r\nStrong Python and SQL (PostgreSQL).\r\nExperience with time-series databases such as TimescaleDB, streaming systems such as Kafka or Kinesis, and observation and reporting systems such as Grafana.\r\nExperience working alongside physics, optics, materials, or hardware engineering teams, and having a clear understanding of physical properties and sensor values and their meaning.\r\nExperience designing and operating production data pipelines, for example Airflow, Dagster, Prefect, or similar.\r\nHands-on experience with cloud data infrastructure, including object storage (S3 or equivalent) and at least one major data warehouse or lakehouse such as Snowflake, Databricks, BigQuery, or Redshift.\r\nA solid grasp of file formats and storage trade-offs across formats like Parquet, Avro, JSON, and HDF5.\r\nPractical experience with data quality, schema evolution, and pipeline observability.\r\nExperience supporting AI/ML workflows as a data engineer, including feature stores, training data management, dataset versioning, and labeling pipelines.\r\nComfort working with engineering and scientific stakeholders to translate vague data needs into durable systems.\r\nStrong communication, and a service-oriented attitude toward downstream consumers of your data.\r\nNice to Haves\r\nExperience with manufacturing or industrial data, such as high-frequency sensor telemetry.\r\nExperience handling large scientific or image-heavy datasets, including CT scans, layer-wise build imagery, melt pool monitoring, thermography, and metrology.\r\nFamiliarity with metal additive manufacturing, particularly laser powder bed fusion or related laser-based processes. Useful concepts include build files, scan paths, process parameters such as laser power, exposure, hatch spacing, and layer thickness, powder handling, melt pool dynamics, and in-situ process monitoring.\r\nFamiliarity with Seurat's broader technology stack, including high-power lasers, optics and photonics, or precision motion systems.\r\nPrior work at a hardware or deep-tech startup, with comfort for the pace and ambiguity that come with bringing new physical products to market.\r\nBenefits\r\nCompetitive salary and meaningful equity.\r\nComprehensive health, dental, and retirement benefits.\r\nThe opportunity to shape the data foundation of a category-defining hardware company.\r\nWork on novel technology with a talented, multidisciplinary team.\r\nA collaborative and supportive work environment.\r\nTo Apply\r\nMassachusetts Salary Range\r\nSalary Range\r\n$130,000—$165,000 USD\r\nSeurat Technologies is an Equal Opportunity Employer that values employees with a broad cross-cultural perspective. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, citizenship status, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.\r\nSee more open positions at Seurat Technologies\r\nJ-18808-Ljbffr","company":"Socket","rawCompany":"socket","city":"Dorchester Center","state":"MA","isRemote":false,"isActive":false,"createdAt":"2026-08-08T01:49:37.623Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Search\r\njobs\r\n1,155\r\nExplore\r\ncompanies\r\n52\r\nJoin talent network\r\nTalent\r\nData Engineer\r\nSeurat Technologies\r\nSoftware Engineering, Data Science\r\nWilmington, MA, USA\r\nUSD 130k-165k / year + Equity\r\nPosted on Jun 22, 2026\r\nAbout Seurat\r\nSeurat is transforming manufacturing for people and our planet by delivering a scalable additive manufacturing solution to fundamentally change how products are made. Seurat's proprietary Area Printing process, developed at Lawrence Livermore National Labs (LLNL), allows metal components to be manufactured at price points and quality levels that compete directly with conventional manufacturing techniques, enabling the reshoring of supply chains and promoting the decarbonization of industry. Seurat has raised over $180M and is backed by leading venture partners like Capricorn, NVentures (NVIDIA), True Ventures, General Motors Ventures, Denso, Porsche SE, SIP global partners, Honda, Xerox Ventures/Myriad Venture Partners, Cubit Capital, Siemens Energy, and Maniv Mobility.\r\nPosition Overview\r\nSeurat is looking for an experienced Data Engineer to own and expand the upstream data foundation behind our process engineering work. The role covers ingestion, cleaning, organization, governance, and access. You will design and operate the pipelines and storage that turn raw output from numerous materials studies, machine qualification trials, application development runs, and customer builds into reliable, well-organized data that engineers, scientists, and downstream analysis or AI/ML systems can rely on.\r\nThis is a platform role. The most common day-to-day work is making our process engineers, data analysts, and ML practitioners more productive by giving them dependable data and good ways to get at it. The role is not focused on analysis or model development, although you will work closely with the people who do that work.\r\nKey Responsibilities\r\nData ingestion and integration\r\nBuild and operate the pipelines that pull in high-volume process data from Seurat's print systems and adjacent equipment.\r\nIntegrate data from heterogeneous sources, including telemetry streams, in-situ process monitoring (optical, thermal, imaging), build job metadata, powder lot and material records, and post-build inspection such as metrology, microscopy, and mechanical tests.\r\nEfficiently store and retrieve large binary artifacts such as images, layer-wise scans, and sensor traces, alongside more structured data.\r\nData cleaning and normalization\r\nAdd validation, deduplication, and normalization so that downstream consumers do not have to keep rediscovering the same data quality issues.\r\nDefine and maintain schemas across data sources whose formats change as the hardware and process evolve.\r\nWork with hardware, process, and software engineers to address data quality problems at the source rather than only in flight.\r\nData lake and storage\r\nDesign and run Seurat's data lakehouse, including partitioning strategies, file formats such as Parquet, HDF5, and Zarr, schema enforcement, retention, and cost management.\r\nBuild catalog and lineage tooling so that engineers can find and understand the data they need without relying on tribal knowledge.\r\nPick the right storage tier for each workload across object storage, time-series, relational, and search systems.\r\nData access and tooling\r\nProvide well-documented access patterns, including query interfaces, APIs, and notebooks, so that process engineers, analysts, and ML practitioners can be productive without becoming infrastructure experts themselves.\r\nManage access control, governance, and auditing sensitive or proprietary data.\r\nBuild internal tooling that lowers the cost of common data tasks, including extraction, joining, exploration, and sharing.\r\nReliability and operations\r\nInstrument pipelines for observability and respond to failures and data quality regressions.\r\nEstablish testing patterns appropriate to data systems, including contract tests, data quality checks, lineage verification, and backfills.\r\nKey Goals and Expected Outcomes\r\nA reliable, well-organized process data foundation. Process and inspection data is ingested, cleaned, and made accessible without ad-hoc effort from downstream consumers.\r\nMeasurable improvements in data quality. Freshness, completeness, and correctness across the most important datasets are tracked and trending in the right direction.\r\nSelf-service. Process engineers, analysts, and AI/ML engineers can answer their own data questions with confidence in the underlying data.\r\nA scalable platform. The data foundation grows with Seurat's print fleet, sensor coverage, and product diversity without requiring proportional headcount.\r\nQualifications\r\nBachelor's degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.\r\n3+ years of professional experience as a Data Engineer or in a closely related role.\r\nStrong Python and SQL (PostgreSQL).\r\nExperience with time-series databases such as TimescaleDB, streaming systems such as Kafka or Kinesis, and observation and reporting systems such as Grafana.\r\nExperience working alongside physics, optics, materials, or hardware engineering teams, and having a clear understanding of physical properties and sensor values and their meaning.\r\nExperience designing and operating production data pipelines, for example Airflow, Dagster, Prefect, or similar.\r\nHands-on experience with cloud data infrastructure, including object storage (S3 or equivalent) and at least one major data warehouse or lakehouse such as Snowflake, Databricks, BigQuery, or Redshift.\r\nA solid grasp of file formats and storage trade-offs across formats like Parquet, Avro, JSON, and HDF5.\r\nPractical experience with data quality, schema evolution, and pipeline observability.\r\nExperience supporting AI/ML workflows as a data engineer, including feature stores, training data management, dataset versioning, and labeling pipelines.\r\nComfort working with engineering and scientific stakeholders to translate vague data needs into durable systems.\r\nStrong communication, and a service-oriented attitude toward downstream consumers of your data.\r\nNice to Haves\r\nExperience with manufacturing or industrial data, such as high-frequency sensor telemetry.\r\nExperience handling large scientific or image-heavy datasets, including CT scans, layer-wise build imagery, melt pool monitoring, thermography, and metrology.\r\nFamiliarity with metal additive manufacturing, particularly laser powder bed fusion or related laser-based processes. Useful concepts include build files, scan paths, process parameters such as laser power, exposure, hatch spacing, and layer thickness, powder handling, melt pool dynamics, and in-situ process monitoring.\r\nFamiliarity with Seurat's broader technology stack, including high-power lasers, optics and photonics, or precision motion systems.\r\nPrior work at a hardware or deep-tech startup, with comfort for the pace and ambiguity that come with bringing new physical products to market.\r\nBenefits\r\nCompetitive salary and meaningful equity.\r\nComprehensive health, dental, and retirement benefits.\r\nThe opportunity to shape the data foundation of a category-defining hardware company.\r\nWork on novel technology with a talented, multidisciplinary team.\r\nA collaborative and supportive work environment.\r\nTo Apply\r\nMassachusetts Salary Range\r\nSalary Range\r\n$130,000—$165,000 USD\r\nSeurat Technologies is an Equal Opportunity Employer that values employees with a broad cross-cultural perspective. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, citizenship status, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.\r\nSee more open positions at Seurat Technologies\r\nJ-18808-Ljbffr","datePosted":"2026-08-08T01:49:37.623Z","dateModified":"2026-08-08T01:49:37.623Z","hiringOrganization":{"@type":"Organization","name":"Socket","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dorchester Center","addressRegion":"MA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"33a71de45b40f67790d428fe"},"url":"https://jobsearcher.com/jobs/33a71de45b40f67790d428fe"}}