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Job Description & How to Apply Below
A.
Key Responsibilities:
Partner with Product Managers to define KPIs, feature success metrics, and measurement frameworks.
Collaborate with Tech Owners to ensure accurate and scalable data instrumentation.
Work closely with Business teams to convert commercial goals into structured, analytics-ready datasets.
Build and maintain ETL/ELT pipelines and reusable data models.
Enable funnel, retention, cohort, and monetization analysis.
Implement and support data lake architecture, covering:
Data at rest (storage, warehousing, governance)
Data in motion (real-time ingestion, streaming, transformation)
Ensure data quality, monitoring, documentation, and governance standards.
B. Required Skills
Strong SQL and hands-on Python expertise.
Experience with modern data warehouses (Snowflake / Big Query / Redshift).
ETL orchestration tools (Airflow / DBT or similar).
Understanding of streaming and real-time data concepts.
Experience working in cross-functional product environments.
C. Critical Requirement – Learning Agility
Readiness and capability to learn and adopt any technology required for the role.
Hands-on across modules required for data lake implementation.
Ability to evaluate, adapt, and implement evolving data technologies as product complexity scales.
D. What We Value
Product-first mindset with strong technical grounding.
Ownership and accountability.
Clear communication with business and technology stakeholders.
Structured thinking and bias for action.
Position Requirements
10+ Years
work experience
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