Data Engineer

Here’s What You’ll Do Day-to-Day:

• Design, build, and optimize scalable ETL/ELT pipelines to facilitate seamless data ingestion and transformation processes.
• Develop and maintain data models to enable self-service analytics and reporting across the organization.
• Optimize database performance in PostgreSQL, ensuring efficient data storage, retrieval, and query execution.
• Implement and enhance search capabilities using NoSQL technologies like ElasticSearch or Solr to improve data discovery.
• Collaborate with data analysts to create insightful dashboards that support data-driven decision-making.
• Ensure data quality, governance, and security by adhering to best practices in cloud-based data environments.
• Monitor and troubleshoot issues within data pipelines, focusing on optimizing efficiency and reliability.
• Work closely with software engineers and product teams to integrate data solutions into operational workflows and product development.

Here’s What You’ll Need to Be Successful:

• 5+ years of experience in data engineering or a similar role, with a proven track record of designing scalable data solutions.
• Expertise in PostgreSQL, including database management, query optimization, and performance tuning.
• Hands-on experience with AWS cloud services such as S3, Lambda, Glue, Redshift, and IAM.
• Proficiency in data warehousing technologies like Snowflake, Redshift, or BigQuery for cloud-based data storage and analysis.
• Strong skills in data transformation, modeling, and building efficient ETL/ELT pipelines.
• Experience with data visualization tools like Mode, Looker, Tableau, or Hex to support analytics and reporting.
• Knowledge of ElasticSearch or Solr for implementing search indexing and query capabilities.
• Proficiency in SQL and Python, with experience in automation, scripting, and workflow orchestration (e.g., Airflow).
• Understanding of CI/CD pipelines, infrastructure-as-code principles, and cloud-based deployment practices.
• Strong analytical and problem-solving abilities, with a passion for leveraging data-driven insights to inform decisions.
• Nice-to-Have: Experience with streaming data solutions like Kafka or Kinesis, knowledge of machine learning pipelines, and familiarity with data privacy regulations such as GDPR or CCPA.

The Interview Process:

• Your application will be reviewed for possible next steps by the Hiring Manager.
• If you meet eligibility requirements, the next step would be a video screen with a member of the PeopleOps team for about thirty (30) minutes.
• If warranted, the next step would be a video interview with our CTO for forty-five (45) minutes.
• If warranted, the next step would be a video panel interview with key stakeholders at PadSplit for one-and-a-half (1.5) hour.
• The panel interview will require a candidate to work on a technical assessment where you will showcase your engineering skills to the panel for discussion. 
• If warranted, then we move to offer!

Compensation, Benefits, and Perks:

• Fully remote position - we swear!
• Competitive compensation package including an equity incentive plan
• National medical, dental, and vision healthcare plans
• Company provided life insurance policy
• Optional accidental insurances, FSA, and DCFSA benefits
• Unlimited paid-time (PTO) policy with eleven (11) company-observed holidays
• 401(k) plan 
• Twelve (12) weeks of paid time off for both birth and non-birth parents
• The opportunity to do what you love at a company that is at the forefront of solving the affordable housing crisis