Description:

PadSplit is hiring for a Data Engineer to build and maintain scalable data infrastructure that drives analytics, reporting, and decision-making across the organization.
This role is critical to optimizing data pipelines, ensuring data reliability, and enabling cross-functional teams to unlock valuable insights in a remote, high-growth environment.
The Data Engineer will design, build, and optimize scalable ETL/ELT pipelines to facilitate seamless data ingestion and transformation processes.
They will develop and maintain data models to enable self-service analytics and reporting across the organization.
The role involves optimizing database performance in PostgreSQL, ensuring efficient data storage, retrieval, and query execution.
The Data Engineer will implement and enhance search capabilities using NoSQL technologies like ElasticSearch or Solr to improve data discovery.
Collaboration with data analysts to create insightful dashboards that support data-driven decision-making is essential.
The position requires ensuring data quality, governance, and security by adhering to best practices in cloud-based data environments.
Monitoring and troubleshooting issues within data pipelines, focusing on optimizing efficiency and reliability, is a key responsibility.
The Data Engineer will work closely with software engineers and product teams to integrate data solutions into operational workflows and product development.

Requirements:

Candidates must have 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, is required.
Hands-on experience with AWS cloud services such as S3, Lambda, Glue, Redshift, and IAM is necessary.
Proficiency in data warehousing technologies like Snowflake, Redshift, or BigQuery for cloud-based data storage and analysis is essential.
Strong skills in data transformation, modeling, and building efficient ETL/ELT pipelines are required.
Experience with data visualization tools like Mode, Looker, Tableau, or Hex to support analytics and reporting is needed.
Knowledge of ElasticSearch or Solr for implementing search indexing and query capabilities is important.
Proficiency in SQL and Python, with experience in automation, scripting, and workflow orchestration (e.g., Airflow) is required.
Understanding of CI/CD pipelines, infrastructure-as-code principles, and cloud-based deployment practices is necessary.
Strong analytical and problem-solving abilities, with a passion for leveraging data-driven insights to inform decisions, are essential.
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.

This is a fully remote position.
The company offers a competitive compensation package including an equity incentive plan.
National medical, dental, and vision healthcare plans are provided.
A company-provided life insurance policy is included.
Optional accidental insurances, FSA, and DCFSA benefits are available.
The position includes an unlimited paid-time off (PTO) policy with eleven company-observed holidays.
A 401(k) plan is offered.
Twelve weeks of paid time off for both birth and non-birth parents is provided.
Employees have the opportunity to do what they love at a company that is at the forefront of solving the affordable housing crisis.