1

Data Stacks Jobs in Raleigh, NC (NOW HIRING)

Data Engineer

Durham, NC ยท On-site

$110K - $132K/yr

By owning the entire stack-from sensing hardware to data infrastructure-we have delivered a breakthrough solution that reveals complex biological and chemical interactions, predicts precision ...

Senior Data Analyst

Raleigh, NC ยท On-site

$110/hr

Experience with cloud platforms (e.g., AWS, Azure, GCP) and modern analytics stacks. * Knowledge of data governance, data quality, and privacy best practices. * Prior experience in EV Charging ...

Experience with cloud platforms (e.g., AWS, Azure, GCP) and modern analytics stacks. * Knowledge of data governance, data quality, and privacy best practices. * Prior experience in EV Charging ...

Experience with cloud platforms (e.g., AWS, Azure, GCP) and modern analytics stacks. * Knowledge of data governance, data quality, and privacy best practices. * Prior experience in EV Charging ...

About the Role We are looking for a Full Stack Software Developer to join our small, high-impact ... Data pipelines and database infrastructure that turn raw charging data into actionable insights ...

About the Role We are looking for a Full Stack Software Developer to join our small, high-impact ... Data pipelines and database infrastructure that turn raw charging data into actionable insights ...

About the Role We are looking for a Full Stack Software Developer to join our small, high-impact ... Data pipelines and database infrastructure that turn raw charging data into actionable insights ...

Experience in a "full-stack" environment - data file ingest, ETL, data storage interaction, application development, communication of results to storage systems, code version control is a plus EPIC ...

Expertise with SQL, R or Python and data visualization tools such as Tableau for full-stack data analysis, insight synthesis and presentation. * Knowledge of and experience in leveraging Applied ...

Senior Full Stack Engineer As a Senior Full Stack Engineer, you'll drive digital transformation and ... NoSQL databases and distributed data systems * Familiarity with Digital Banking and financial ...

next page

Showing results 1-20

Data Stacks information

What are Data Stacks?

Data stacks refer to the combination of tools, technologies, and frameworks used to collect, store, process, and analyze data within an organization. A typical data stack might include data ingestion tools, databases, data warehouses, processing frameworks, and analytics platforms. The purpose of a data stack is to streamline the flow of data from its source to actionable insights, supporting business intelligence and decision-making. Common examples include the Modern Data Stack, which often uses tools like Fivetran, Snowflake, dbt, and Looker.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need strong skills in database design, data modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with tools such as SQL, Apache Spark, Hadoop, and cloud platforms like AWS or Google Cloud, as well as certifications in these technologies, is highly valued. Problem-solving abilities, attention to detail, and effective communication are important soft skills for this role. These skills are crucial for building reliable data pipelines, ensuring data quality, and supporting data-driven decision-making within organizations.

What is the difference between Data Stacks vs Data Analysts?

AspectData StacksData Analysts
Required CredentialsBachelor's in Computer Science, Data Science, or related fields; certifications like SQL, Python, or cloud platformsBachelor's in Statistics, Mathematics, or related fields; often certifications in Excel, SQL, or data visualization tools
Work EnvironmentTechnical teams, data engineering, software development environmentsBusiness units, reporting teams, data visualization platforms
Employer & Industry UsageTech companies, data-driven organizations, startupsFinance, marketing, healthcare, consulting firms

Data Stacks focus on building and managing the underlying data infrastructure, while Data Analysts interpret data to provide insights. Both roles require analytical skills, but Data Stacks professionals are more technical, working with data pipelines and databases, whereas Data Analysts focus on analyzing data to support decision-making.

What are some common challenges faced when managing modern data stacks, and how can they be addressed in this role?

Professionals managing modern data stacks often encounter challenges such as integrating diverse data sources, ensuring data quality, and maintaining system scalability as data volumes grow. Addressing these challenges typically involves collaborating closely with data engineers, analysts, and IT teams to implement robust data pipelines, automate data validation, and monitor system performance. Staying updated with evolving technologies and best practices is also crucial for proactive problem-solving and optimizing the data stack for business needs.

Data Engineer

Sennos

Durham, NC โ€ข On-site

$110K - $132K/yr

Full-time

Posted 28 days ago


Job description

About Sennos
Sennos is rapidly emerging as the global leader in AI-driven sensing, analytics, and control for the Fluid, Fermentation, and Bio-manufacturing industries. With a revolutionary integration of hardware, software, and real-time multi-parametric data, we have quietly built the world's most advanced sensing system and largest AI-powered fermentation data warehouse. By owning the entire stack-from sensing hardware to data infrastructure-we have delivered a breakthrough solution that reveals complex biological and chemical interactions, predicts precision outcomes, and enables next-generation production control.
Sennos is a rapidly growing start-up looking for someone who can quickly adapt to a changing environment and who has the desire to grow with us!
Position Summary
The Data Engineer sits within the Data & Analytics organization and supports the development and ongoing improvement of Sennos' modern data platform. This role focuses on building and maintaining data pipelines, implementing transformations, and contributing to a reliable Snowflake-based warehouse that powers analytics, reporting, machine learning, and product capabilities.
Working closely with senior data engineering leadership, data architecture, analytics engineering, and product teams, this role combines hands-on technical execution with growing exposure to data modeling, quality enforcement, and scalable platform development.
Responsibilities
  • Build and maintain ETL/ELT pipelines using SQL and Python under the guidance of senior data engineering leadership
  • Develop and maintain transformations using dbt or similar tools within a Snowflake-based warehouse
  • Create and optimize datasets and views to support analytics, reporting, machine learning, and product feature development
  • Manage ad hoc data requests with accuracy and efficiency while maintaining data integrity and consistency
  • Implement and maintain data quality checks, validation rules, and testing processes to ensure reliability and trust in warehouse data
  • Support the enforcement of data contracts between source systems and the warehouse
  • Assist in reverse ETL workflows to operationalize warehouse data into downstream systems
  • Contribute to ML data preparation and feature pipeline workflows
  • Collaborate closely with Data Architecture, Analytics Engineering, Product, and Software Engineering teams
  • Contribute to documentation, governance practices, and continuous improvement of data engineering standards

Required Qualifications
Education:
  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent years of professional experience)

Experience:
  • 2-4 years of experience in data engineering or a related data-focused role
  • Experience working with ETL/ELT processes and structured warehouse data
  • Exposure to cloud-based data platforms (AWS preferred)

Skills:
  • Strong SQL skills (joins, window functions, and query optimization fundamentals)
  • Proficiency in Python for data processing, scripting, or automation
  • Familiarity with version control systems (e.g., Git)
  • Strong attention to detail and commitment to data accuracy
  • Ability to troubleshoot and debug data workflows effectively
  • Strong written and verbal communication skills
  • Ability to collaborate across technical and non-technical teams

Preferred Qualifications
  • Experience working with Snowflake or similar cloud data warehouses
  • Exposure to dbt or similar transformation frameworks
  • Introductory experience with dimensional modeling concepts
  • Experience implementing data quality tests or validation frameworks
  • Exposure to data contracts or schema management practices
  • Familiarity with reverse ETL concepts
  • Passing experience with workflow orchestration tools (e.g., Airflow, Dagster, or similar)
  • Familiarity with CI/CD practices for data workflows
  • Experience using AI-assisted tools to support debugging, pipeline development, or data engineering workflows
  • Exposure to BI tools (e.g., Power BI, Tableau, Looker)

Team Working Style
  • Collaborative and supportive, with strong mentorship from senior data engineering leadership
  • Focused on building durable foundations while moving quickly to meet evolving needs
  • Values curiosity, precision, and continuous skill development

Physical Requirements and Work Environment
  • Ability to sit for extended periods while working at a computer
  • Office setting with remote/hybrid flexibility
  • Minimal travel required (occasional team meetings or company events)

This job description is intended to convey information essential to understanding the scope of the position and is not an exhaustive list of skills, efforts, duties, responsibilities, or working conditions associated with it. Responsibilities may change according to business needs.
Our company is currently active in 16 states (AZ, GA, ID, IL, FL, MA, ME, MI, MO, NC, NY, TN, TX, OR, VA, and WA), and we prefer candidates located in one of these states for remote positions.
Equal Opportunity Statement
Sennos is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Please Note
Applicants must be permanently authorized to work for ANY employer in the United States. We are unable to sponsor or take over sponsorship of an employment visa at this time.
Recruitment Agency Notice:
We do not accept unsolicited candidate submissions. We only work with recruitment agencies that have a signed agreement with our HR team. Unsolicited resumes will not incur any fee obligation.