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Randomtrees
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Gcp Data Engineer -DBT

Gcp Data Engineer -DBT

Randomtrees

5 - 10 years

25 - 37 Lacs

hyderabad chennai

Posted:1 week ago| Platform:

Apply

Skills Required

airflow bigquery dbt sql python pubsub data flow dataproc

Work Mode

Hybrid

Job Type

Full Time

Job Description

Job Title: GCP Data Engineer

Location: Hyderabad & Chennai (Hybrid mode of working)

Experience: 5+ Years

Employment Type: Full Time

Key Responsibilities

Design, build, and optimize scalable
data pipelines
using
GCP services
(
Big Query, Dataflow, Airflow, Pub/Sub, Cloud Storage
).
Develop and maintain
ETL/ELT workflows
leveraging
Airflow
and
DBT
for data modeling and transformations.
Write and optimize complex
SQL queries
Big Query
BigQuery
.
Implement
data integration
solutions to ingest structured, semi-structured, and unstructured data from multiple sources.
Work closely with data analysts, data scientists, and business stakeholders to ensure reliable and timely data delivery.
Apply
Python programming
for building automation, orchestration, and custom data engineering solutions.
Monitor, troubleshoot, and enhance existing pipelines with a focus on
scalability, performance, and cost optimization
.
Ensure adherence to
data governance, security, and compliance standards
.

Required Skills & Experience

5+ years of hands-on experience as a
Data Engineer
with a focus on
GCP ecosystem
.
Strong experience in
Advanced SQL
(complex joins, window functions, query optimization, partitioning, clustering).
Proficiency in
Python programming
for data pipelines, automation, and integration.
Strong working knowledge of
BigQuery, Dataflow, Airflow, and DBT
.
Experience with
ETL/ELT pipeline design, data modeling (snowflake/star schema), and performance tuning
.
Good understanding of
CI/CD, Git, and DevOps practices
in data engineering.
Ability to work in
hybrid mode
across
Hyderabad/Chennai
.

Good to Have

Experience with
Terraform
or IaC for GCP resources.
Knowledge of
Kubernetes, Cloud Functions, or Data Fusion
.
Exposure to
streaming data pipelines
using Pub/Sub, Kafka, or similar.

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