Data Engineer

Work Experience- 6 to 10 years

Skills:- Python, PySpark, SQL, AWS, Redshift, DyanamoDB, Airflow

Mode of Working- Work from office(Hyderabad)

Primary Skills (Must have)
Advanced SQL with strong query‑tuning skills on a cloud data warehouse (Snowflake strongly preferred).

Python for ELT (Airflow or Dagster DAGs, custom API ingestors, pandas/polars transforms).
dbt end‑to‑end: staging → mart models, Jinja macros, freshness & schema tests, docs generation.

Hands‑on experience ingesting marketing sources: Google Ads, Meta Ads, LinkedIn, GA4 BQ export, HubSpot or Salesforce, Stripe/Chargebee.

Data‑quality automation using

Great Expectations or dbt tests with Slack / PagerDuty alert routing.

Secure credential management (AWS KMS, Vault, OAuth flows) and PII masking / role‑based access control.

Git‑based CI/CD for data code, zero‑downtime migrations, environment promotion.

Secondary Skills( Good to have)
Streaming ingestion (Kafka, Kinesis, Pub/Sub) and Spark / Databricks for large backfills.

Metric‑layer tools (dbt Metrics, Cube) and vector stores (pgvector, Pinecone) for schema search.

Terraform for data‑infra IaC; cost‑monitoring / FinOps on Snowflake or Redshift.

Exposure to privacy and compliance frameworks (GDPR, SOC‑2) and consent metadata handling.

Certifications: SnowPro Core or Advanced, AWS Data Analytics Specialty, dbt Advanced.

Qualifications (Education/Certifications)
BS/BE in Computer Science, Information Systems, Data Engineering, or equivalent practical experience.

6+ years of cloud data‑engineering

Proven track record shipping production ELT pipelines in a marketing or revenue‑analytics environment.

Nice‑to‑have credentials: AWS Certified Data Analytics – Specialty, dbt Advanced, Airflow DAG Author.

Job Types: Full-time, Permanent

Pay: ₹400,000.00 - ₹1,800,000.00 per year

Work Location: In person