Synechron
GCP Data Engineer | Expertise in Cloud Data Solutions, ETL Pipelines & Open-Source Technologies
Job Summary
Synechron is seeking a dedicated GCP Data Engineer to support the design, development, and deployment of scalable data solutions on Google Cloud Platform. This role is vital within our data team to enable data-driven decision-making by providing robust, efficient, and innovative data pipelines and analytics infrastructure. The GCP Data Engineer will collaborate with cross-functional teams to implement best practices and leverage cutting-edge cloud technologies to meet client and business needs.
Software Requirements
Required Software Proficiency:
Google Cloud Platform (GCP) services (BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub) — hands-on experience and strong familiarity with core services
SQL and NoSQL databases (e.g., BigQuery, Cloud SQL, Firestore) — expertise in data management and query optimization
Programming languages: Python, Java, or Scala — proficient in developing data pipelines and automation scripts
Open-source data tools and frameworks (e.g., Apache Beam, Apache Airflow, Kafka) — practical experience
Data integration tools (e.g., Talend, Informatica, or similar) — experience in data ingestion and ETL processes
Preferred Software Skills:
Machine learning frameworks (TensorFlow, scikit-learn) — exposure beneficial
Data visualization and BI tools (Tableau, Data Studio) — familiarity advantageous
Cloud deployment and automation tools (Terraform, Cloud Deployment Manager) — experience preferred
Overall Responsibilities
Collaborate with clients and internal teams to understand business data requirements and translate them into scalable cloud data solutions
Design, build, test, and deploy data pipelines and data lakes utilizing GCP services
Optimize data workflows for performance, cost efficiency, and reliability
Ensure data security, privacy, and compliance across all cloud data infrastructure
Conduct data quality checks and troubleshoot technical issues proactively
Participate in code and design reviews, maintaining high standards of quality and security
Share knowledge related to emerging cloud data technologies and best practices within the team
Technical Skills (By Category)
Programming Languages:
Essential: Python, Java, or Scala — advanced proficiency for data pipeline development
Preferred: Additional languages such as SQL and scripting languages
Databases/Data Management:
Essential: BigQuery, Cloud SQL, Firestore — robust understanding and management experience
Preferred: NoSQL and other cloud-native storage systems
Cloud Technologies:
Essential: Google Cloud Platform core services, cloud security, and cost management
Preferred: Multi-cloud experience or exposure to other cloud services (AWS, Azure)
Frameworks and Libraries:
Essential: Apache Beam, Dataflow, Airflow for workflow orchestration and ETL pipelines
Preferred: TensorFlow or ML frameworks for integrated analytics solutions
Development Tools and Methodologies:
Essential: CI/CD (Cloud Build, Jenkins), Git, Agile/Scrum practices — proven experience in collaborative project environments
Security Protocols:
Awareness of data governance, encryption, and compliance standards in cloud data engineering
Experience Requirements
Minimum of 8+ years of experience in data engineering or related roles, with practical experience on GCP
Demonstrated expertise in building and managing large-scale data pipelines, analytics, and storage solutions
Experience working with cross-functional teams using Agile methodologies
Strong track record of delivering secure, scalable, and efficient data solutions on cloud platforms
Alternative experience includes extensive hands-on data engineering in similar cloud environments or open-source projects
Day-to-Day Activities
Develop and maintain data pipelines, workflows, and analytics infrastructure using GCP tools
Engage with clients and internal stakeholders to gather requirements and deliver suitable data solutions
Perform data ingestion, transformation, and validation to ensure high data quality
Troubleshoot and resolve technical issues, ensuring minimal disruption to data services
Conduct reviews and optimize existing data architectures for cost and performance improvements
Document processes, provide technical guidance, and share insights on emerging data engineering trends
Qualifications
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (Master’s preferred)
Relevant certifications such as Google Cloud Professional Data Engineer or equivalent are a plus
Commitment to continuous learning on evolving cloud data technologies and best practices
Professional Competencies
Strong analytical and problem-solving skills to address complex data challenges
Effective communication skills for engaging with technical and non-technical stakeholders
Ability to work collaboratively within diverse teams and adapt to fast-changing environments
Active learning attitude, staying current with the latest cloud and data engineering advancements
Results-oriented mindset focused on delivering impactful, high-quality data solutions
Organizational skills to prioritize tasks effectively and meet project deadlines
SYNECHRON’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.
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