Senior Data Engineer

Atlassian•Washington, DC

23h•$138,942 - $218,550•Hybrid

About The Position

Our Product DE organization is looking for a Senior Data Engineer reporting to the Senior Data Engineering Manager. You will be responsible for designing premier data architecture and solutions that drive strategic decision-making. Beyond technical execution, you will collaborate with business stakeholders to translate operational needs into technical requirements and spearhead initiatives to improve overall system efficiency.

Requirements

A BE in Computer Science or equivalent with 6+ years of professional experience as a Data Engineer or in a similar role
Experience building scalable data pipelines in Spark using Airflow scheduler/executor framework or similar scheduling tools.
Experience with Databricks and its APIs.
Experience with modern databases (Redshift, Dynamo DB, Mongo DB, Postgres or similar) and data lakes.
Proficient in one or more programming languages such as Python/Scala and rock-solid SQL skills.
Champion automated builds and deployments using CICD tools like Bitbucket, Git
Experience working with large-scale, high-performance data processing systems (batch and streaming)
Experience working for SAAS companies

Nice To Haves

Experience with Machine Learning
Committed code to open source projects
Experience building self-service tooling and platforms

Responsibilities

Partner across engineering organizations to spearhead and execute high-impact, company-wide initiatives.
Mentor and upskill junior engineers, fostering a culture of technical excellence and continuous growth.
Collaborate with leadership, product engineers, program managers, and data scientists to deeply understand and prioritize business data requirements.
Leverage deep technical expertise to design and architect scalable, high-performance data solutions.
Develop, launch, and optimize highly efficient, reliable ELT/ETL pipelines capable of processing both large-scale and specialized datasets.
Intelligently design robust data models optimized for high-speed storage, accessibility, and downstream retrieval.
Implement and deploy rigorous data quality frameworks to guarantee data accuracy, freshness, and trust.
Maintain full technical ownership of the end-to-end data engineering lifecycle for your team's solutions.
Participate in the team’s on-call rotation to ensure platform stability and support operational health.
Partner with software engineering teams to design and build next-generation data systems that enable rapid, self-service data consumption.