WHO YOU’LL WORK WITH

You will report to the Data Engineering Manager and work hand-in-hand with the data engineering squad and product management team along with a variety of dedicated Converse and Nike partners focused on technology solution delivery, data architecture, and analytics platforms. You will join a highly motivated, global team that will be a driving force in building Data and Analytic solutions for the Converse Enterprise.

WHO WE ARE LOOKING FOR

We are looking for someone who thrives in the ever-evolving world of data & analytics. The right candidate can quickly pick up new programming languages, technology concepts, and frameworks. They have strong problem-solving skills and an understanding of data structures and algorithms. They thrive in a hard-working team environment and have an ability to lead, influence and communicate effectively with team members and business stakeholders alike. Experience must include:

• Bachelor’s degree or equivalent combination of education, experience or training
• Minimum 6 years of relevant work experience in designing and implementing innovative data engineering capabilities and end to end solutions.  

• Advanced Experience with data modeling, warehousing and building ETL pipelines; Must have experience with any ETL tools, preferably Matillion and/or PySpark
• Expert in building/operating highly available, distributed systems of data extraction, ingestion, processing of large data sets and delivering end to end projects independently
• Advanced experience building cloud scalable, real-time and high-performance data lake solutions, preferably Databricks, Snowflake, AWS
• Advanced Experience with big data technologies such as: Hadoop, Hive, Spark, EMR and orchestration tools like Airflow
• Advanced experience in SQL and modern scripting or programming languages, such as Python, Shell
• Experience in CI/CD Pipeline for Code deployment: preferred GitHub, Jenkins, terraform, Databricks Assets Bundles

WHAT YOU’LL WORK ON

As a Lead Data Engineer on the Converse Enterprise Data & Analytics team, you will be primarily accountable for setting development standards and frameworks for the Converse Data Engineering team. This role will take a hands-on approach, implementing standard development processes that will be used across the data engineering squads to increase the team’s velocity and the overall quality of data pipelines. This role will also be responsible for designing and developing critical data pipelines and streamlining our data architecture while ensuring data quality and reliability throughout the data lake and data warehouse. Role responsibilities are:

• Define and communicate the requirements for technical environments and determine the technical scope for projects, and provide technical estimates or capacity planning; Translate product backlog items into engineering designs and logical units of work
• Assess a well-defined problem and lead the development of a technical solution that meets the needs of the business and aligns with architectural standards
• Drive collaboration with architecture, platform teams or other teams on integration needs/designs; create advanced technical designs; approve proof of concept efforts and reviewing results; ensure high quality solutions are implemented, and engineering standard methodologies are defined and followed.
• Design and implement data products and features in collaboration with product owners, data analysts, and business partners using Agile / Scrum methodology.
• Define and apply appropriate data acquisition, processing and consumption strategies for given technical scenarios; Design and implement distributed data processing pipelines using tools and languages prevalent in the big data ecosystem; Profile and analyze data for the purpose of designing scalable solutions
• Drive and implement the technical strategies of new data projects and the optimization of existing solutions; Troubleshoot complex data issues and perform root cause analysis to proactively resolve product and operational issues
• Build utilities, user defined functions, libraries, and frameworks to better enable data flow patterns; implement complex automated routines using workflow orchestration tool
• Drive collaborative reviews of design, code and test plans and dataset implementation by other data engineers in support of maintaining data engineering standards
• Identify and remove technical bottlenecks for your engineering squad; and provide leadership, guidance and mentorship to other data engineers in adopting best standards and practices
• Anticipate, identify and tackle issues concerning data management to improve data quality; Build and incorporate automated unit tests and participate in integration testing efforts.
• Utilize and advance the software engineering best practices, including source control, code review, testing, and continuous integration and delivery (CI/CD) on the required cloud infrastructure and workspace configurations, Source files, such as notebooks and Python files, that include the business logic etc.

These are the characteristics that we strive for in our own work. We would love to hear from candidates who embody the same:

• Desire to work closely with your teammates to come up with the best solution to a problem
• Demonstrate experience and ability to deliver results on multiple projects in a fast-paced, agile environment
• Excellent problem-solving and interpersonal communication skills;
• Strong desire to learn, share knowledge with others and coach the team.

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.