Description
We are looking for an experienced SQL Data Analyst to support our US partner cllent. The day-to-day tasks will primarily involve pulling and analyzing reports on large data sets.
This is a great opportunity for someone who has e-commerce experience and wants continuous learning and growth in their career.
Offer: PHP90,000 - PHP 105,000
The Benefits:
- 100% Work From Home
- Attendance, Performance, and Referral Bonuses
- Paid Holidays and Time Offs
- Health Insurance
- Continuous Learning and Development
- Bi-weekly salary payout
- Work-Life Balance
Core Tasks:
- Write, optimize, debug SQL queries; create joins, aggregations, and subqueries
- Pull and utilize data across Meta, Google, Shopify, Google Sheet/Excel
- Data manipulation (i.e., sorting, scrubbing, tagging, cleaning, de-duping)
- Build reports and dashboards from scratch or using provided templates
- Analyze results and write a summary of reports
- Create reports for partners upon request
- Provide daily/ weekly/ monthly reporting on various performance and marketing data sets
- Validate and troubleshoot existing reports for data/logic accuracy
- Perform other ad-hoc data analysis tasks as needed
Must Haves:
- 2-4 years of experience in complex data analysis
- Has experience in SQL SME and autonomous work
- With intermediate to advanced skills in MS Excel/Google Sheets
- Has demonstrated ability in generating ad-hoc reports and dashboards from scratch
- With a strong ability to write, optimize, and debug SQL queries; experience creating joins, aggregations, and subqueries
- With familiarity in general data warehouse infrastructure, specifically with Snowflake, Fivetran, Sigma)
- Experienced in creating/managing dashboards in a BI tool (Sigma is a plus)
- With basic e-commerce knowledge (KPIs such as CAC, ROAS); familiarity with Shopify
- With great English skills (oral and written)
- Familiarity with Slack and Gmail
- With recent experience working in the graveyard shift and amenable to working in PST
Nice to have:
- Bonus: Ability to both pull and analyze data + make efficiency suggestions
- Familiar with automation and tech stack integrations; able to suggest and implement automation
- Experience wtih inventory data analysis
