Manager, Data Engineering

Company Description

Merkle is a leading technology-enabled, data-driven customer experience management (CXM) company. For over 30 years, Fortune 1,000 companies and leading nonprofit organizations have partnered with us to build and maximize the value of their customer portfolios. With more than 9,600 smart, dedicated people in more than 50 offices around the world, we are still growing at a rate that outpaces the market, with 2019 net revenue of $1.1 billion.

Job Description

As a Manager of Data Engineer, you will lead a data engineering team: developing new or enhancing existing data products as we build a meta data driven, big data solution, processing and transforming data to produce high quality data assets for our customers.   You will work with passionate, goal-oriented Data Engineers to solve complex problems.  You will collaborate with Operations and Delivery teams to provide market focused data solutions to our customers. You will provide hands on technical leadership, guiding, coaching, and mentoring for your global team members, managing and assigning technical workloads, and ensuring we continuously improve and deliver high quality solutions.  You will lead and grow a high performing data engineering team that embraces change, is continuously improving, and rapidly builds, tests, enhances, and scales data transformational solutions that drive incremental business value for our customers and partners.

Key Responsibilities:

• Create or assemble large, complex data sets that meet functional and non-functional business requirements
• Document requirements from End Users to development user stories, capturing all the details and acceptance criteria required
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data builds, and implementing data QA and reporting
• Coordinate with cross-functional teams, such as Identity and Data Science teams, to develop directional roadmaps, develop new data products, and manage priorities to meet business needs, ensuring each team has the data required
• Manage to a budget, including infrastructure, software, and cloud-based costs
• Provide hands on daily coaching and mentoring to team members, offering strong analytical, problem solving, and troubleshooting expertise and guidance
• Review designs, code, plans, strategies, etc. as well as assess data results with a high attention to detail to ensure we deliver high quality solutions
• Assess, recommend, and implement improvements in processes and procedures, evaluating new approaches, industry standards, new tooling, etc.
• Grow and lead motivated, high performing team members that produce high quality solutions, meeting goals and delivering results
• Collaborate with Product Management and IT to create and maintain a strong working environment for development including infrastructure and agile processes
• Leads the development of Proof of Concepts for new or updated data assets
• Triage data build or release issues as required
• Support integration with internal solutions

Qualifications

• Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science or other equivalent experience
• 10+ year experience with data engineering, data modeling and/or data processing
• 8+ years’ experience in leading teams
• 8+ years’ or equivalent experience in developing and implementing production grade systems, applications, or big data solutions
• 5+ years’ experience with SQL, relational databases, and data warehouses
• Experience with Python
• Experience with Snowflake
• Experience in cloud base technologies (AWS, GCP, Azure)
• Experience working in Agile teams and CI/CD environments
• Experience with Linux; experience with Windows is a plus
• Experience with Jenkins, Airflow, or other orchestration tools
• Experience with code repositories such as Git, Bitbucket, Github, etc.
• Experience in Tableau is a plus

Skills:

• Strong analytic skills working with B2B, B2C, and Digital data assets for the purposes of customer experience marketing and analytics
• Able to perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Able to build processes supporting data transformation, data structures, metadata, dependency and workload management
• Demonstrated ability to manipulate, process and extract value from large disconnected datasets
• Demonstrated strong organizational, leadership, and communication skills
• Familiarity with statistical concepts, modeling, and the ability to integrate data and analytics 

• Able to motivate and inspire while instilling accountability and delive