Senior Software Engineer - Data Engineering

Position Overview

The Senior Software Engineer - Data Engineering is responsible for improving data pipelines, building monitoring and reliability solutions, and ensuring good data governance. This role is crucial within the Data Engineering team, leading a revamp of analytical foundations.

Employment Type: Full-Time

Reports to: Engineering Manager

Responsibilities

• Lead the design, development, and refactoring of critical data pipelines to reduce failures and improve efficiency.
• Implement comprehensive monitoring, alerting, and service level agreement tracking to achieve and maintain high operational uptime.
• Resolve data pipeline issues, contributing to faster incident resolution.
• Contribute to the development, implementation, and adoption of data governance standards across critical datasets.
• Ensure data quality and integrity throughout the data lifecycle.
• Enforce governance standards on core pipelines.
• Participate in the redesign and deployment of core subject areas within our analytical data model to improve clarity, utility, and support business reporting needs.
• Establish dashboard curation standards to improve usability and user satisfaction.
• Eliminate unused or inefficient tasks within our data processing frameworks.
• Develop structured data extractors for various application use cases.
• Contribute to compute cost reduction efforts through task reconfiguration and the implementation of efficient incremental data processing strategies.
• Develop mechanisms to make application engineers aware of potential breaking changes to data schemas.

Qualifications

• Experience: 5+ years of hands-on experience in data engineering, with a strong focus on building and maintaining scalable and reliable data pipelines (ETL/ELT).
• Data Warehousing & Modeling: Proven experience with data warehousing concepts, data modeling (e.g., dimensional, relational), and building analytical datasets.
• Technical Skills:
  • Proficiency in Python and SQL.
  • Experience with data pipelining tools like Spark/PySpark and dbt.
  • Experience with platforms like AWS, Databricks, or Google Bigquery.
  • Proficiency in version control (Github) and CI/CD tools (CircleCI).
• Data Governance & Quality: Experience with data governance principles, data quality management, and data security.
• Monitoring & Alerting: Experience implementing monitoring and alerting for data pipelines.
• BI Tools: Familiarity with BI tools (Looker and LookML) and how data is consumed for analytics and reporting.
• Collaboration: Experience working with non-technical teammates to identify dataset requirements.

Physical/Cognitive Requirements

• Capability to remain seated in a stationary position for prolonged periods.
• Eye-hand coordination and manual dexterity to operate keyboard, computer, and other office-related equipment.

Compensation & Benefits

• Pay Range: $138,380 - $254,111+ equity + benefits (United States new hire base salary target)
  • The starting base salary will depend on factors such as education, training, skills, years and depth of experience, certifications, licensure, organizational needs, internal peer equity, and geographic/market data.
  • Compensation structures and ranges are tailored to specific geographic zones to ensure fair and equitable compensation. Your Recruiter can share your geographic zone upon inquiry.
• Benefits & Perks:
  • Remote-first culture
  • 401(k) savings plan through Fidelity
  • Comprehensive medical, vision, and dental coverage through multiple medical plan options
  • Disability insurance
  • Paid Time Off ("PTO")

Application Instructions

• Information not provided in the original job description.

Company Information

• Information not provided in the original job description.