Data Engineer
New
S
SunPowerSolar Energy
In-office - Orem, UT, or Philippines (remote), Comfortable working across time zonesFull-TimeSenior
SalaryOrem, UT: $105,000 - $130,000 base, DOE | Philippines: PHP 2,500,000 - 4,000,000 annually (approx. $40,000 - $65,000 USD equivalent), DOE
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Job Details
- Languages
- English (for candidates based in the Philippines)
- Experience
- 3+ years
- Required Skills
- PythonSQLETLSalesforceSnowflakeAirflowNetSuiteBigQuerydbt
Requirements
- 3+ years of experience building and maintaining data pipelines in a production environment.
- Strong SQL skills.
- Hands-on experience with at least one modern ETL/ELT tool or framework (e.g., Fivetran, dbt, Airflow, custom Python pipelines).
- Working knowledge of Python or another scripting language for data processing.
- Experience with a cloud data warehouse (Snowflake, BigQuery, Redshift, or similar).
- Understanding of data modeling fundamentals and best practices for pipeline reliability and testing.
- Demonstrated experience in using AI for data pipes and reporting solutions.
- Comfortable working across time zones and collaborating with a distributed team.
- Strong English communication skills for candidates based in the Philippines.
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent practical experience.
- Experience integrating data from CRM/ERP systems (Salesforce, NetSuite) a plus.
Responsibilities
- Design, build, and maintain ETL/ELT data pipelines that move data between source systems (Salesforce, NetSuite, HR/payroll systems, etc.) and the data warehouse.
- Monitor pipeline health, troubleshoot failures, and resolve data quality issues proactively.
- Partner with analysts and business stakeholders to understand data needs and design reliable, well-documented data models.
- Support integration of data from newly acquired companies into SunPower's central data platform.
- Implement data validation, testing, and monitoring practices to catch issues before they reach reporting.
- Optimize pipeline performance and cost as data volume grows.
- Maintain clear documentation of data sources, transformations, and pipeline architecture.
- Collaborate with IT and security on data governance, access controls, and compliance requirements.
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