Senior Manager, Data Engineering

Introduction

In this role, you will be responsible for planning and overseeing the Data Services Data Engineering and Machine Learning teams engaged in enterprise-wide data projects to ensure they are completed in a timely fashion and within budget. You will plan and designate project resources, monitor progress, and keep stakeholders informed the entire way. This role will be supporting the charge in implementing D&A technologies and principles and will act as a single point of contact for data engineering processes to ensure the team is delivering impactful and useful solutions.

Job Responsibilities

• Leads both operational and directional aspects for the data engineering team
• Make high-judgement decisions around technology, strategy, execution approach, and personnel
• Exercise supervision of group in terms of costs, methods, performance, and staffing
• Accountable for team’s consistent delivery of high quality, on time work; dependencies and impacts have been vetted and mitigated upon final delivery
• Responsible for employee life cycle, including advising hiring manager by screening and interviewing candidates, on-boarding, goal alignment, work assignment and addressing skill gaps for each team member.
• Collaborate within and across departments to clear roadblocks, facilitate progress, and enable team to deliver on their commitments
• Builds team with healthy dynamics
• Upholds department and company policies and reinforces them when necessary
• Champion clean, simple, methodical, and ethical data engineering practices
• Create and maintain optimal data pipeline architecture 
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Support the data science team by preparing data for prescriptive and predictive modelling.

Knowledge and Experience

• 7+ years of experience as a Data Engineer or in a similar role
•  Experience in managing a team of Data Engineers
• Experience with Data modelling, Data warehousing, and building ETL pipelines
• Experience with AWS (S3, EKS, EC2, RDS) or similar cloud services, Snowflake, Fivetran, Airbyte, dbt, Docker, Argo
• Experience in SQL, Python and Terraform
• Experience with building Data pipelines and applications to stream and process datasets
• Robust understanding of DevOps principals is required
• Experience managing cloud infrastructure would be beneficial
• Sound knowledge of distributed systems and Data architecture (lambda)- design and implement batch and stream Data processing pipelines, knows how to optimize the distribution, partitioning, and MPP of high-level Data structures
• Knowledge of Engineering and Operational Excellence using standard methodologies
• Expertise in designing systems and workflows for handling Big Data volumes
• Knowledge of Data management fundamentals and Data storage principles
• Strong problem-solving skills and ability to prioritize conflicting requirements
• Excellent written and verbal communication skills and ability to succinctly summarize key findings.

Education

Bachelor’s Degree or equivalent work experience