scientist/data engineer

NetSource, Inc.

United States

12 days ago

Role details

Contract type

Contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

0 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Microsoft Excel Amazon Web Services Data Analysis Spreadsheets Cloud Database Information Engineering Extract Transform Load (ETL) Data Mapping Data Migration Data Systems Relational Databases Database Queries

+21 more

Query Languages Failure Mode Effects Analysis Python (Programming Language) Laboratory Information Management Systems Raw Data Software Tools Cloud Services SAP (Applications) SQL Databases Data Streaming Technical Data Management Systems Strategies of Testing Workflow Management Systems JMP (Statistical Software) Enterprise Software Applications Snowflake Git Kubernetes Information Technology Software Version Control Data Pipelines

Job description

Design, build, test, document, and maintain end-to-end data pipelines that ingest data from multiple source types, including relational databases, enterprise systems, spreadsheets/CSV files, structured and semi-structured datasets, and other approved data sources.
Develop scalable ETL/ELT workflows that load raw data into governed environments, transform data into validated staging/intermediate/analytics-ready layers, and support traceability, reporting, and technical decision-making.
Use tools such as Snowflake, dbt, SQL, Python, AWS, and workflow/orchestration platforms to create modular, tested, version-controlled, and maintainable data models and pipelines.
Support the MSAT Material Science team on materialrelated investigations and deviation analyses: gather and analyze manufacturing and analytical data, contribute to technical assessments, and help implement solutions as applicable.
Assist MSAT Material Science in developing and revising raw material specifications: draft language, define acceptance criteria, compile technical justification, compendial review and coordinate SME deliverables.
Support material qualification and requalification activities on behalf of the MSAT Material Science team: prepare qualification plans/protocols, coordinate testing with internal or external labs/vendors, analyze returned data, and draft qualification reports.
Provide technical input for change controls: prepare technical assessments, perform impact and risk evaluations, coordinate verification/validation activities, and compile evidence for closure.
Support technology transfer activities: prepare transfer documentation, align material requirements between development and manufacturing, and coordinate posttransfer monitoring and followup.
Contribute to material traceability and data mapping initiatives by partnering with Process, Planning, Manufacturing, Quality, Supply Chain/Procurement, Supplier Quality, and IT/data teams to connect raw material, supplier, quality, and manufacturing data and produce reliable datasets, dashboards, and actionable visualizations.
Interface with Supplier Quality and Procurement to support vendor qualification, incoming material review, sample evaluations, and supplier investigations.
Prepare and maintain regulatorygrade documentation on behalf of MSAT Material Science: investigation summaries, specifications, test method rationales, SOPs, qualification packages, and technical reports
Support audits and inspections by preparing evidence, supporting response to technical queries, and assisting in closure of materialrelated findings under Quality oversight.
Communicate findings and recommendations to the MSAT Material Science team, crossfunctional partners, and leadership; present at technical meetings as required., MSAT Material Science is seeking a scientist/data engineer who can enter the role with intermediate-to-advanced data engineering capability and immediately contribute to the design, build, validation, and maintenance of end-to-end data pipelines. This role requires strong SQL skills, hands-on experience querying relational databases, and practical experience moving data from multiple source formats and systems-including relational databases, flat files, structured and semi-structured datasets, enterprise systems, and cloud data platforms-into reliable, governed, analytics-ready data products. Experience with modern data engineering tools such as Snowflake, dbt, Python, AWS, orchestration/workflow tools, and data quality testing is strongly desired. The scientist/data engineer will collaborate closely with IT/data teams and business SMEs to define data requirements, establish secure and scalable data flows, support traceability initiatives, and ensure pipelines are reliable, auditable

Requirements

Advanced degree in Materials Science, Chemical Engineering, Chemistry, Polymer Science, Computer Science or closely related discipline preferred; Master’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’'’s with 3-5+ years experience.
PhD with 0-3+ years experience.
Intermediate-to-advanced data engineering skills are required, including strong SQL proficiency, relational database querying, data modeling concepts, and experience building or supporting production-quality data pipelines.
Hands-on experience with modern data stack tools such as Snowflake, dbt, Python, AWS, Git/version control, ETL/ELT frameworks, workflow orchestration, and data quality testing is strongly preferred.
Demonstrated ability to work with data from varied formats and systems, including relational databases, CSV/Excel files, structured and semi-structured datasets, LIMS/MES/SAP or other enterprise systems, and cloud-based data warehouses.
Experience coordinating testing with external/internal analytical labs and interpreting lab reports.
Knowledge of GMP principles, validation strategies, and risk assessment methodologies (e.g., FMEA).
Familiarity with supplier qualification practices and vendor communications.
Demonstrated experience supporting material investigations, specification setting, qualification oversight, change control, and tech transfer in a regulated manufacturing environment (pharma, biotech, medical device, or related) preferred.
Strong data analysis skills and ability to synthesize manufacturing and analytical datasets to support root cause and risk assessments.
Proven technical writing skills for regulatorygrade reports, specifications, and protocols.
Experience collaborating with IT/data engineering teams and cross-functional partners to define data requirements, troubleshoot source-system issues, align on access/security expectations, validate outputs, and deploy governed data solutions.
Familiarity with electronic quality systems (eQMS, LIMS), manufacturing systems (MES), SAP and common data tools (Excel, Python/R, JMP, or similar).
Curiosity and willingness to learn the broader MSAT Material Science scope, including raw material investigations, specification development, qualification, change control, technology transfer support, and regulated technical documentation.
Prior industry experience in MSAT or material science support roles within regulated manufacturing preferred., and fit for use in a regulated manufacturing environment. In addition to the data engineering focus, the candidate must be willing and able to learn the broader MSAT Material Science responsibilities described below, including raw material quality, investigations, specifications, material qualification, change control, technology transfer support, analytical method evaluation, and regulatory-quality documentation.