Senior Manager, Data Engineering

At Optimizely, we're on a mission to help people unlock their digital potential. We do that by reinventing how marketing and product teams work to create and optimize digital experiences across all channels. With Optimizely One, our industry-first operating system for marketers, we offer teams flexibility and choice to build their stack their way with our fully SaaS, fully decoupled, and highly composable solution.


We are proud to help more than 10,000 businesses, including H&M, PayPal, Zoom, and Toyota, enrich their customer lifetime value, increase revenue and grow their brands. Our innovation and excellence have earned us numerous recognitions as a leader by industry analysts such as Gartner, Forrester, and IDC, reinforcing our role as a trailblazer in MarTech. 

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

Optimizely is committed to a diverse and inclusive workplace. Optimizely is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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