GCP Data Engineer

Relanto; Fremont (CA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Relanto in Fremont, CA is seeking a Data Engineer to design and maintain scalable data pipelines on Google Cloud Platform. You will leverage Python, SQL, PySpark, BigQuery, and Airflow to enable analytics across teams and support data-driven decisions.

You will collaborate with data analysts and engineers to optimize transformations, queries, and data quality, while practicing CI/CD, Terraform, and container-based deployments in a hybrid work setup.

Qualifications

• Hands-on experience with Python and SQL required.
• Experience with PySpark and distributed data processing.
• Strong knowledge of BigQuery and GCP services.
• Experience with Apache Airflow for orchestration.
• Hands-on experience with dbt for data transformation and modeling.
• Understanding of ETL/ELT frameworks and data warehousing concepts.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Python and PySpark.
• Build and optimize ETL/ELT workflows using Apache Airflow.
• Develop data transformation models and workflows using dbt.
• Work with BigQuery for data warehousing, querying, and optimization.
• Write efficient SQL queries for large-scale data processing.
• Ensure data quality, integrity, and reliability across pipelines.
• Collaborate with Data Analysts, Data Scientists, and business stakeholders for data requirements.
• Monitor and troubleshoot production data workflows and resolve issues proactively.
• Implement best practices for logging, monitoring, testing, and CI/CD.

Skills

Python

SQL

PySpark

BigQuery

Airflow

dbt

ETL/ELT frameworks

CI/CD

Git

GCP

Education

Bachelor’s degree in Computer Science or related field

Tools

Terraform

Docker

Kubernetes

Git

Job description

Location: Fremont, CA (3 days a week hybrid)

We are looking for a skilled Data Engineer with proven experience in building and maintaining scalable data pipelines and cloud-based data platforms on Google Cloud Platform (GCP). The ideal candidate should have hands‑on expertise in Python, SQL, PySpark, BigQuery, Airflow, and modern ETL/ELT frameworks

.The role involves working closely with analytics, business, and engineering teams to enable reliable and scalable data solutions

.

Responsibiliti

• esDesign, develop, and maintain scalable data pipelines using Python and PySpa
• rkBuild and optimize ETL/ELT workflows using Apache Airfl
• owDevelop data transformation models and workflows using d
• btWork with BigQuery for data warehousing, querying, and optimizati
• onWrite efficient and optimized SQL queries for large-scale data processi
• ngEnsure data quality, integrity, and reliability across pipelin
• esCollaborate with Data Analysts, Data Scientists, and business stakeholders for data requiremen
• tsMonitor and troubleshoot production data workflows and resolve issues proactive
• lyImplement best practices for logging, monitoring, testing, and CI/
• CDOptimize cloud resource usage and cost efficiency on G
• CPParticipate in code reviews and engineering best practic

es

Required Ski

• llsStrong hands‑on experience with Python and
• SQLExperience with PySpark and distributed data process
• ingGood knowledge of BigQuery and GCP servi
• cesExperience with Apache Airflow for orchestrat
• ionHands‑on experience with dbt for data transformation and model
• ingUnderstanding of ETL/ELT frameworks and data warehousing conce

pts

Familiarity with GCP services such

• as:BigQ
• rageData
• procComp
• oserPub
• /SubExperience with Git and CI/CD pract
• icesStrong analytical and problem‑solving sk

ills

Good to

• HaveExposure to streaming pipelines using Kafka or Pu
• b/subUnderstanding of data governance and security con
• ceptsExperience with Terraform or Infrastructure as
• CodeKnowledge of containerization (Docker/Kubern

etes)

Preferred Qualifi

• cationBachelor’s degree in Computer Science, Engineering, or related