Data Engineer (Data Warehouse Focus)
Turing • Remote
Education
Not stated
Type
Hourly
Listed
24d ago
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From the Turing listing
Job Title: Data Engineer (Data Warehouse Focus)
Domain: BFSIExperience: 5-8 YearsLocation:Gurugram, Haryana - 3 days WFOEmployment Type: Full-Time
Job Summary
Seeking a Data Engineer with strong expertise in Snowflake, Python, Airflow, and SQL to design, build, and maintain scalable cloud-based data warehouse solutions for BFSI platforms.
Key Responsibilities
- Design and develop data warehouse architectures and ETL/ELT pipelines.
- Build and orchestrate workflows using Python, SQL, Airflow, PySpark, Kafka, Databricks.
- Perform data modeling, validation, and governance in regulated BFSI environments.
- Migrate data from legacy systems to AWS/Azure cloud platforms.
- Create analytics and reports using Power BI, Tableau, Alteryx.
- Collaborate with data science teams to productionize ML features.
- Ensure performance, reliability, and operational excellence.
Required Skills
- Core: Snowflake, Python, SQL, Airflow
- Data & Cloud: Oracle/PostgreSQL/MySQL/SQL Server, AWS (S3, EMR), Azure (ADLS, ADF, Databricks)
- Big Data: Kafka, Databricks
- BI & Tools: Power BI, Tableau, Alteryx, dbt, Git
- Methodology: Agile (Scrum/Kanban)
BFSI Experience
- Strong experience in Banking, Financial Services, or Insurance.
- Knowledge of financial data models, compliance, security, and regulatory reporting.
Education
- MCA / BSc / BE / BTech in Computer Science or related field.
Nice to Have
- Exposure to Pandas, NumPy, SciPy
- Snowflake or Cloud certifications
Requirements
- Must be eligible to work in Remote
- Fluent proficiency in English (Written & Verbal)
- Reliable high-speed internet connection
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
Sample questions for a Data Warehouse Engineer role, written in-house to help you prepare.
How do you decide between a star schema and a more normalized model when designing a data warehouse?
I lean toward a star schema when the primary use case is reporting and analytics, since the denormalized structure keeps queries simpler and faster for end users. I only introduce more normalization where storage costs or update anomalies genuinely outweigh the query performance benefit.
What's your approach to building an ETL pipeline that needs to handle both historical backfills and ongoing incremental loads?
I design the pipeline so incremental loads and backfills share the same transformation logic, just with different source windows, rather than maintaining two separate code paths that can drift out of sync. I also make sure the incremental logic is idempotent so a rerun doesn't duplicate data.
How do you approach optimizing a query that's become slow as the underlying table has grown?
I start by checking the query plan to see where time is actually being spent, rather than guessing at the fix, and I look at whether partitioning or indexing aligned with the common filter columns would help before considering a full redesign of the table.
What's your process for validating that a new ETL pipeline is producing correct data before it goes live?
I reconcile totals and row counts against the source system for a representative sample period, and I check edge cases like nulls and duplicate keys specifically, rather than only spot checking a few rows that look fine. I keep the validation checks running as part of the pipeline going forward, not just as a one time gate.
This listing calls for these tools directly. Prep for the technical screen:
What to Expect
Looking at Turing Software Engineering listings we've tracked, contracts in this domain typically run about 8.4 weeks. Actual length varies by project, but this gives you a realistic baseline going in.
Based on 28 extracted Turing Software Engineering listings.
Why this role
This Data Engineer (Data Warehouse Focus) position asks for solid Software Engineering knowledge. The AI training workflow itself gets taught on the job.
Skills and categories
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Common questions
How and when does Turing pay contractors?
Monthly, in USD, via Deel, Payoneer, or direct bank transfer. You're engaged as an independent contractor responsible for your own local taxes. Plan your cash flow around a monthly cycle if you're used to weekly payouts elsewhere.
Do I need to be a software engineer to work for Turing?
No, not anymore. Turing built its name matching senior engineers with Silicon Valley companies, but it has since expanded into AGI infrastructure work and now hires non-engineering domain experts, technical writers, and researchers for post-training data annotation and RLHF. A strong analytical background and excellent English matter more than coding ability.
What does task-based AI training work look like?
Practical, hands-on data work: recording short videos, categorizing images, rating text responses, or analyzing data. Tasks are designed to be short and distinct, typically 5 to 60 minutes each.
What does asynchronous AI training work mean in practice?
No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.
What does Software Engineering work look like for a Data Engineer (Data Warehouse Focus)?
Tasks here are scoped to Software Engineering, not generic labeling. As a Data Engineer (Data Warehouse Focus), expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Software Engineering) rather than following a one-size-fits-all rubric. If you don't have hands-on Software Engineering background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Coding, SQL, and Python are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.
How much does this specific role pay?
The listing doesn't state a rate. The $25–$55/hr shown here is our estimate from the role type and location (see /pay-methodology), so treat it as a rough guide and confirm the actual rate with the platform before committing time.
What happens when I click Apply on this listing?
You'll be taken to Turing's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.