Google Cloud Platform Data Engineer

GCP Data Engineer with Cloud-Native Architecture and Lakehouse Expertise

Job Summary
Synechron is seeking a skilled and experienced Google Cloud Platform (GCP) Data Engineer to lead data architecture, pipeline development, and cloud data solutions supporting enterprise analytics and digital initiatives. This role involves designing, building, and optimizing scalable, secure data pipelines leveraging GCP native services such as BigQuery, Dataflow, Dataproc, and Pub/Sub. The candidate will work within cross-functional teams to implement modern lakehouse architectures, facilitate data streaming, and support enterprise data strategies aligned with organizational goals and regulatory standards.

Software Requirements

• Required:

  • Hands-on experience with GCP data services, including BigQuery, Dataflow, Dataproc, and Datastream

  • Proficiency in Python for data pipeline development, orchestration, and automation

  • Strong SQL skills for data modeling, validation, and query optimization in BigQuery and related databases

  • Experience in building and managing scalable data pipelines and workflows on GCP

  • Familiarity with GCP-native architecture components: Pub/Sub, IAM, Data Catalog, and data streaming solutions

• Preferred:

  • Experience with Delta Lake and lakehouse architectures within cloud ecosystems

  • Knowledge of data governance, security, and compliance in cloud environments

  • Exposure to AI-enabled data solutions and data science frameworks

  • Experience utilizing orchestration tools such as Cloud Composer (based on Apache Airflow)

Overall Responsibilities

• Design, deploy, and optimize scalable and secure data pipelines using GCP data services such as BigQuery, Dataflow, and Dataproc.

• Collaborate with data analysts, data scientists, and business stakeholders to translate data needs into reliable cloud data architectures.

• Manage end-to-end data workflows, including ingestion, transformation, and storage, ensuring high data quality and processing efficiency.

• Implement and monitor data validation routines, ensuring data accuracy, security, and compliance with data governance policies.

• Automate and orchestrate data workflows using Cloud Composer, Dataflow, and other automation tools to enhance operational efficiency.

• Support enterprise data lakes, data warehouses, and Lakehouse architectures, ensuring high performance and cost-effectiveness.

• Troubleshoot pipeline issues, perform root cause analysis, and optimize data processes continually.

• Support cloud infrastructure security controls, access management, and compliance standards.

• Stay current with industry advancements in cloud data management, analytics, and data engineering best practices.

Technical Skills (By Category)

• Data Platform & Storage (Essential):

  • GCP data services: BigQuery, Dataflow, Dataproc, Datastream, Cloud Storage, Pub/Sub

  • Familiarity with Lakehouse architectures, Delta Lake, and data lifecycle management

• Data Processing & Automation (Essential):

  • Python scripting for data pipeline development and automation

  • SQL queries and data validation techniques in big data environments

• Cloud & Architecture (Essential):

  • GCP native architecture, including IAM, data streaming, security policies, and data governance

• Orchestration & Workflow Management (Preferred):

  • Cloud Composer (Apache Airflow) and Dataflow pipeline orchestration

• Development & CI/CD (Preferred):

  • Infrastructure as Code (Terraform, Deployment Manager)

  • CI/CD pipelines via Jenkins, GitLab CI, or similar tools

• Data & Analytics (Preferred):

  • Familiarity with data lakes, data warehouses, and Delta Lake integrations

Experience Requirements

• 3+ years supporting or developing data pipelines on GCP cloud environments.

• Proven experience designing scalable, secure, and high-performance data architectures within cloud ecosystems.

• Hands-on experience with GCP's data services: BigQuery, Dataflow, Dataproc, Pub/Sub, and DataStream.

• Strong Python and SQL skills for data processing, modeling, and validation.

• Knowledge of enterprise data governance, security, and compliance standards in cloud environments.

• Supporting experience supporting financial or regulated industry data projects is a plus.

• Alternative pathways include extensive hands-on experience in cloud data processing, lakehouse architectures, and enterprise big data solutions.

Day-to-Day Activities

• Design, develop, and optimize scalable data pipelines across cloud platforms.

• Collaborate with data teams and stakeholders to understand data requirements and deliver cloud-based solutions.

• Automate data extraction, transformation, and loading workflows to improve efficiency and reliability.

• Monitor data pipeline health and performance, troubleshoot issues, and implement enhancements.

• Support data lake, warehouse, and lakehouse architecture deployment, ensuring security and compliance.

• Conduct root cause analysis for data processing failures and performance bottlenecks.

• Implement and maintain security controls, data privacy standards, and governance policies.

• Engage with industry trends and emerging cloud data technologies to recommend strategic improvements.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.

• 3+ years of experience working in cloud data environments, specifically GCP.

• Deep knowledge of GCP data services: BigQuery, Dataflow, Dataproc, DataStream, Pub/Sub.

• Strong Python and SQL skills for data pipeline development and management.

• Certifications in GCP (e.g., Google Cloud Professional Data Engineer, Architect) are advantageous.

• Experience designing and implementing lakehouse architectures or Delta Lake solutions is a plus.

• Proven ability to support large-scale data infrastructure with security, compliance, and operational excellence.

Professional Competencies

• Critical thinking and problem-solving skills to troubleshoot data pipeline challenges.

• Ability to work independently and within cross-functional teams.

• Strong communication to translate complex data needs into technical solutions.

• Adaptability to evolving cloud platforms, tools, and industry standards.

• Ownership of data quality, security, and operational efficiency.

• Continuous learner committed to staying updated on cloud data management innovations.

S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Candidate Application Notice

Experience Level

Senior Level