Sr Data Engineer
Porch (company site, opens in a new tab)5+ yrsRemoteDirect career pageEst. 24.75–34.65 LPA
Posted on 15 Sept
Reach people at Porch
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Porch you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Build, optimize, and maintain ETL/ELT data pipelines using Google Cloud technologies (BigQuery, Dataflow, Cloud Composer) supporting business intelligence and reporting.
- Develop and refine data models (Star/Snowflake schema) and high-performance SQL scripts handling complex data transformations with focus on accuracy and efficiency.
- Collaborate with stakeholders to translate business metrics into technical specifications and proactively resolve data pipeline bottlenecks optimizing query speed and cloud costs.
Minimum Requirements
- 5+ years of professional experience in data engineering with cloud-based data warehouses.
- Strong expertise in Google Cloud ecosystem tools including BigQuery, Cloud Storage, and IAM.
- Expert-level SQL skills including window functions, recursive CTEs, and query plan analysis.
- Ability to work US Eastern Standard Time core hours overlap (7:30pm-11:30pm IST) with a dedicated quiet workspace and reliable internet connection (50 Mbps minimum).
Ideal Candidate Profile
- Experienced in data engineering roles within SaaS and/or insurance domains with familiarity of related metrics (e.g., MRR, Churn, Premiums, Claims).
- Proven track record collaborating with US-based business teams in publicly traded companies or similar environment.
- Strong focus on data integrity and clean code with ability to balance new development and legacy troubleshooting in a team-based setting.