Senior Associate, Data Enablement

dentsu•Detroit, MI

8d•$65,000 - $75,000•Hybrid

About The Position

As part of the Data team, the Senior Associate, Data Enablement role is responsible for ensuring accuracy, consistency, and reliability across the full data lifecycle. This position blends practical data engineering skills with a strong focus on data quality, process improvement, and support for business and analytics needs. The role helps maintain clean, well-structured data by validating inputs, monitoring workflows, and ensuring outputs meet organizational standards. Responsibilities include supporting data ingestion processes, refining pipelines, and enabling clear, trusted data for internal teams and global partners.

Requirements

Bachelor's degree in Analytics, Statistics, Mathematics, Computer Science, or a related field
At least 1-2 years required in data enablement, data engineering, analytics engineering, or a related field.
At least one year of strong working knowledge of SQL and Python to build, automate, and validate data pipelines, perform analysis, and troubleshoot data quality issues across large datasets.
Experience with ETL/ELT tools or workflow oriented systems.
Familiarity with Microsoft’s data ecosystem (e.g., data storage, reporting, or workflow tools).
Experience using version control for managing code and collaborating on data related changes.
Experience integrating external or third party data sources.
Understanding of data quality practices, including validation checks, monitoring, and reconciliation.
Ability to communicate clearly with both technical and non-technical partners.
Demonstrated ability to learn quickly, solve ambiguous problems, and work independently.
Strong organizational and time management skills.

Responsibilities

Design and manage processes for capturing and ingesting data from multiple sources.
Maintain and improve ETL/ELT workflows to ensure they run efficiently and reliably.
Work with data models and structured schemas to support clear and consistent reporting.
Validate and monitor data throughout pipelines, including checks for completeness, accuracy, and structural consistency.
Create and maintain alerts, checks, and dashboards to help identify issues early.
Help document and support data governance practices related to data intake and processing.
Translate technical workflows into clear outputs, dashboards, and resources for end users.
Collaborate with analysts, media teams, and business partners to ensure data structures meet their needs.
Support and enhance internal tools that surface data quality issues and provide visibility to stakeholders.
Assist in managing mapping tables, error logs, data lineage references, and validation checks.
Contribute to developing and maintaining data pipelines and related tools within the organization’s technology stack.
Use version control to manage changes, maintain transparency, and support team collaboration.
Help identify opportunities for automation that improve consistency and reduce manual workload.
Maintain thorough documentation to support transparency, continuity, and team alignment.
Collaborate with teammates to improve processes, scale data operations, and create a positive experience for data consumers.