The Senior Software Engineer - Data Engineering will improve data pipelines, build monitoring and reliability solutions, and ensure good data governance.
This role is crucial within the Data Engineering team, leading a revamp of analytical foundations and reporting directly to the Engineering Manager.
Responsibilities include leading the design, development, and refactoring of critical data pipelines to reduce failures and improve efficiency.
The engineer will implement comprehensive monitoring, alerting, and service level agreement tracking to maintain high operational uptime.
They will resolve data pipeline issues to contribute to faster incident resolution and develop, implement, and adopt data governance standards across critical datasets.
Ensuring data quality and integrity throughout the data lifecycle and enforcing governance standards on core pipelines is essential.
The role involves participating in the redesign and deployment of core subject areas within the analytical data model to improve clarity and support business reporting needs.
Establishing dashboard curation standards to enhance usability and user satisfaction is also part of the job.
The engineer will eliminate unused or inefficient tasks within data processing frameworks and develop structured data extractors for various application use cases.
They will contribute to compute cost reduction efforts through task reconfiguration and efficient incremental data processing strategies.
Developing mechanisms to inform application engineers of potential breaking changes to data schemas is also required.
Requirements:
Candidates must have 5+ years of hands-on experience in data engineering, focusing on building and maintaining scalable and reliable data pipelines (ETL/ELT).
Proven experience with data warehousing concepts, data modeling (e.g., dimensional, relational), and building analytical datasets is required.
Proficiency in Python and SQL is necessary.
Experience with data pipelining tools like Spark/PySpark and dbt, as well as platforms like AWS, Databricks, or Google Bigquery, is essential.
Candidates should have experience with data governance principles, data quality management, and data security.
Experience implementing monitoring and alerting for data pipelines is required.
Familiarity with BI tools (Looker and LookML) and understanding how data is consumed for analytics and reporting is necessary.
Proficiency in version control (Github) and CI/CD tools (CircleCI) is required.
Experience working with non-technical teammates to identify dataset requirements is essential.
Benefits:
The position offers a remote-first culture, allowing for flexible work arrangements.
A 401(k) savings plan through Fidelity is included in the benefits package.
Comprehensive medical, vision, and dental coverage through multiple medical plan options, including disability insurance, is provided.
Paid Time Off (PTO) and Discretionary Time Off (DTO) are part of the benefits.
The role includes 12 weeks of 100% Paid Parental leave.
Family Building & Compassionate Leave benefits include fertility coverage, $25,000 for surrogacy/adoption, and paid leave for failed treatments, adoption, or pregnancies.
Work-From-Home reimbursement is available to support team collaboration in home office work.
