Data Engineer

Insight Global; Newark (DE); On-site; USD 100,000 - 150,000; Full time

Job summary

Insight Global is seeking a data engineer to design and maintain SQL-based datasets and data models to support marketing use cases in Newark, DE preferred. The role focuses on data discovery, profiling, and building analytics-ready datasets.

You will collaborate with Marketing Operations and Marketing Analytics to enable audience creation, campaign execution, and executive reporting, while ensuring data quality and documentation.

Qualifications

• 3-5 years of experience in data engineering or analytics.
• Ability to write queries in scratch in SQL.
• Proficiency in Python.
• Understanding of how data supports multiple business functions (marketing, infra, credit, product).
• Familiarity with marketing data concepts: campaigns, segmentation, testing, measurement.

Responsibilities

• Design, build, and maintain SQL-based datasets, views, and data models that support marketing use cases.
• Source, profile, and research data in the data warehouse to make it campaign-ready.
• Engineer end-to-end data solutions from ingestion through business consumption.
• Support identity-based and customer-level data use cases (e.g., prequalification strategies, audience growth).
• Partner with Marketing Operations to enable audience creation, campaign execution, and customer experiences.
• Collaborate with Marketing Analytics to explain data structures and support executive reporting.
• Translate business questions into technical requirements and scalable data solutions.
• Present findings, trends, and insights back to marketing stakeholders in a clear way.
• Build dashboards and visualizations showing trends and segment performance.
• Develop internal monitoring dashboards to detect data issues and quality problems.
• Support testing, validation, and quality checks prior to deployment.
• Coordinate with testing/deployment teams to move solutions into production.
• Contribute to documentation, governance, and ongoing improvements of marketing data assets.

Skills

SQL

Python

Data modeling

Stakeholder comms

Marketing data concepts

Tools

Snowflake

AWS

Job description

Location: Newark, DE preferred. Otherwise Indianapolis, IN

Duration: 6 mo to hire

Must Haves:

• 3-5 years of experience
• Ability to write queries in scratch in SQL
• Python
• Understanding of how different business functions, such as marketing, infrastructure, credit, product, and data teams, use data in their day-to-day work.
• This person should understand the core concepts within each business domain, the data those teams rely on, why that data exists, and how it can be used to support different business needs. For example, in marketing, this could include campaigns, customer segmentation, testing, and measurement.

Plusses:

• Experience working with marketing teams
• Experience working with Customer Data Platforms (CDI/CDP) or identity resolution vendors Familiarity with identity stitching and customer-level data unification
• Snowflake database
• AWS

Responsibilities:

• Design, build, and maintain SQL-based datasets, views, and data models that support marketing use cases.
• Source, profile, and research data already living in the data warehouse to make it campaign-ready.
• Engineer new data solutions end-to-end, from ingestion through business consumption.
• Support identity-based and customer-level data use cases (e.g., prequalification strategies, audience growth, net-new identification).
• Business Partnership & Strategy
• Partner directly with Marketing Operations to enable audience creation, campaign execution, and customer experiences.
• Collaborate with Marketing Analytics to explain data structures, create new analytical layers, and support executive-level reporting.
• Translate business questions into technical requirements and scalable data solutions.
• Present findings, trends, and insights back to marketing stakeholders in a clear and compelling way.
• Build dashboards and visualizations that show trends, population shifts, and segment performance.
• Develop internal monitoring and control dashboards to detect data issues (e.g., population changes, load failures, anomalies).
• Support testing, validation, and quality checks prior to deployment.
• Operational Support
• Coordinate with internal testing and deployment teams to move solutions into production.
• Contribute to documentation, governance, and ongoing improvements of marketing data assets.
• Day-to-Day Breakdown
• ~60%: Data discovery, profiling, research, and business alignment.
• ~20%: Dashboarding and data visualization.
• ~10%: Testing, audits, and data quality controls.
• ~10%: Administrative work and coordination.