Data Engineer

Posted 2 Months Ago
Hiring Remotely in Maryland, USA
Remote
Mid level
HR Tech • Professional Services • Security
The Role
Design, build, and maintain cloud data infrastructure and ETL/ELT pipelines using Microsoft data technologies. Develop and optimize T-SQL scripts and star-schema data models, support data quality, governance, and security, and participate across the full lifecycle from requirements to deployment and monitoring.
Summary Generated by Built In

It's fun to work in a company where people truly BELIEVE in what they're doing!
We're committed to bringing passion and customer focus to the business.

At Cisive, our vision is to make securing the right talent effortless. We provide technology-first background screening, identity verification, and continuous monitoring solutions that help organizations hire and manage their workforce with confidence.

Our Values

·       Integrity First: We uphold the highest ethical standards in everything we do.

·       Innovate Fearlessly: We challenge the status quo, embrace emerging technologies, and continuously refine our solutions to stay ahead of industry needs.

·       Win Together: We break down barriers, share knowledge, and champion teamwork across departments, brands, and global offices to achieve our collective goals.

·       Customer Obsessed: We go beyond transactional interactions to become trusted partners in risk mitigation and workforce management.

·       Stay One Step Ahead: We proactively seek knowledge that helps us—and our clients—stay ahead of the curve.

Job Description:

Data Engineer (Microsoft Stack)

Join our collaborative Data and AI team, where every member's contributions are valued and visible. As a Data Engineer, you'll take on meaningful responsibilities that directly impact our projects and business at Cisive. This is an excellent opportunity for someone eager to work hands-on with Microsoft's cloud-native data technologies, develop new skills in modern data platforms, and be recognized for their achievements. You'll be supported by experienced professionals and have opportunities to showcase your work in cutting-edge cloud environments.

Responsibilities:

  • Collaborate with the Data and AI team to design and build data infrastructure, including ETL/ELT pipelines using Azure Data Factory.

  • Develop and maintain data models, cloud data warehouses, and data lakes using Azure SQL Server, and Azure SQL Database

  • Write and optimize T-SQL scripts, stored procedures, and functions for data transformation and integration.

  • Support data quality, governance, and security initiatives.

  • Participate in the full lifecycle of data projects, from requirements gathering to deployment and monitoring.

Qualifications:

  • (Required) 3+ years of data engineering experience, preferably with Microsoft data technologies.

  • (Required) Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.

  • (Required) Strong SQL skills and experience with Microsoft SQL Server.

  • (Required) Proficiency in modern coding practices, including Visual Studio Code, Git, and test frameworks (unit testing, regression testing, etc.).

  • (Required) Experience with Azure Data Factory, SSIS, and/or other Microsoft Azure data services.

  • (Required) Experience designing and implementing star schema data models.

  • (Nice to Have) Experience with Databricks and Python

  • Excellent problem-solving skills, attention to detail, and strong communication skills.

  • Ability to work effectively in a team environment and manage multiple tasks with minimal supervision.

What We Offer:

  • Hands-on experience with real-world data engineering projects using Microsoft’s data stack.

  • Mentorship and guidance from experienced data professionals.

  • Opportunities to take on significant responsibilities and make a tangible impact.

  • A collaborative and inclusive work environment.

  • Flexible/remote work options.

Skills Required

  • 3+ years of data engineering experience
  • Bachelor's degree in Computer Science, Data Science, Information Systems, or related field
  • Strong SQL skills and experience with Microsoft SQL Server (T-SQL)
  • Experience developing ETL/ELT pipelines
  • Experience with Azure Data Factory
  • Experience with SSIS and/or other Microsoft Azure data services
  • Proficiency with Visual Studio Code, Git, and test frameworks (unit/regression testing)
  • Experience designing and implementing star schema data models
  • Experience with Databricks
  • Experience with Python
  • Excellent problem-solving skills, attention to detail, and strong communication skills
  • Ability to work effectively in a team and manage multiple tasks with minimal supervision

Cisive Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cisive and has not been reviewed or approved by Cisive.

  • Flexible Benefits — Remote work options and flexible arrangements are highlighted as a clear advantage. Some roles also provide equipment for home offices.
  • Retirement Support — A 401(k) company match is included in the benefits package, supporting long-term savings. The specific match percentage is not publicly detailed.
  • Leave & Time Off Breadth — PTO, paid holidays, and floating holidays are part of the offering. Parental leave is also listed, expanding time-away options.

Cisive Insights

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The Company
HQ: Easton, MD
787 Employees
Year Founded: 1977

What We Do

Cisive is a global provider of compliance-driven human capital and risk management solutions. The company delivers employee onboarding and pre-employment background screening, employment intelligence, and industry-specific data services to large enterprises, particularly in regulated and risk-sensitive sectors. Its offerings support clients in healthcare, financial services, transportation, telecommunications, utilities, and home services, with dedicated in-country account management focused on accuracy, compliance, and customer satisfaction.

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