Manager, Analytics Data Engineering

As the Manager, Analytics Data Engineering, you will spearhead a team tasked with designing, developing, and upholding the organization's data infrastructure. Guiding the efforts of Analytics Data Engineers, you'll blend data engineering expertise with business intelligence methods to swiftly meet our clients' reporting needs. Collaborating closely with Manager, Campaign Analytics and Marketing Science, you'll orchestrate the creation of reports, analyses, extracts, and datamarts seamlessly integrated into Power BI.

This pivotal role centers on data processing within cloud environments like Snowflake, Azure, and AWS, with a keen eye on ensuring Quality Assurance across Power BI and marketing platforms. Alongside overseeing work processes such as automating ad hoc procedures and managing ETL steps, you'll play a crucial role in nurturing talent through training, code reviews, and feedback sessions to enhance the team's skills and deliverables.

Leveraging your expertise in data engineering, leadership, and project management, you'll drive data-driven decision-making to support our business objectives effectively.

Effective data management fuels organization, productivity, and automation. Enabling internal consumers access to trusted data for running queries, developing strategic insights, and delivering standardized outputs. Adding value to our external customers and improving the bottom line.

• Collaborates with their Director and other Managers in the Analytics organization, taking the lead on projects with both internal and external stakeholders to capture requirements, architect, scope, standardize, and document Butler/Till’s data frameworks.
• Architects and writes scripts for the creation, support, and automation of standardized, scalable, and client specific data marts.
• Observes and voices opportunities where work with other departments would create solutions to improve agency efficiency.
• Works closely with B/T’s Analysts, Media, and Account teams to understand our clients’ data needs and the standardization of campaign/ad naming conventions across clients.
• Maintains documentation on existing data policies, data dictionaries, metadata and ETL processes and creates proof of concept (POC) designs for strategic initiatives.

Data Engineering minimizes potential errors by establishing processes and policies for usage and building trust in the data being used to make decisions across the organization. With reliable, up-to-date data, our teams can respond more efficiently to market changes and customer needs.

• Designs automated QA processes of data, acting as a 1st line of defense of data integrity.
• Partners with Analytics for resolving tickets and processing files.
• Designs and maintains data flows in 3rd party applications that monitor data inconsistencies and deficits and builds automated alerts to the team for corrective action.
• Act as a subject matter expert with respect to B/T’s data deliverables as well as advise Campaign Analytics and Marketing Science with utilization strategies of data from our marketing platforms (Google, Facebook, etc.).
• Provides guidance and training to Data Engineers on QA best practices with live code reviews.

Effective data engineering protects our enterprise from data losses, thefts, and breaches with authentication and encryption tools. Strong data security ensures that vital company information is backed up and retrievable should the primary source become unavailable. Also, security becomes more important if data contains personally identifiable information that must be carefully managed to comply with consumer protection laws.

• The Manager of Data Engineer is familiar with data collection policies, both nationally and internationally (i.e. CCPA (California Consumer Privacy Act), GDPR).
• Recommends policies and standards for all supported data processes.
• Provides directions on which data, processes, and database code to troubleshoot for security concerns and designs policies, code, and processes to close security gaps.

Data management best practices allow organizations to effectively scale their usage of data with repeatable processes to keep data and metadata up to date. When processes are easy to repeat, organizations save time, money, and gain efficiency.

• Subject matter expertise on the available data for analytics, analyses, and modeling, working closely with Campaign Analytics and Marketing Science Leadership to create strategic data marts that are easily repeatable for new and existing initiatives.
• Expertise in no/low code solutions (i.e. Microsoft Power Automate, Excel), SQL, and Python to support scalable, full life cycle solutions to meet business needs.
• Engages with vendors and internal stakeholders to explore opportunities to enhance the existing tech stack. Creates well-documented requirements for internal or external stakeholders.
• Orchestrates tests for new software…