GCP Data Engineer | BigQuery, Dataflow & Python

GCP Data Engineer | BigQuery, Dataflow & Python

Job Summary
Synechron is seeking a skilled GCP Data Engineer to design, develop, and optimize data pipelines and cloud-based data solutions on Google Cloud Platform. This role focuses on building scalable data architectures, leveraging GCP services, and collaborating with data engineers, analysts, and business stakeholders to enable data-driven decision making. The ideal candidate will combine strong technical acumen with effective collaboration, drive cloud-native data strategies, and contribute to governance and security practices aligned with enterprise standards.

Software Requirements

Required Skills (Essential)

• Proficiency in Google Cloud Platform (GCP) data services for building and operating data pipelines (e.g., BigQuery, Dataflow/Beam, Cloud Storage, Pub/Sub)

• Strong SQL skills and experience with data modeling and data validation for data warehouse and analytics workloads

• Experience programming in Python or Java for data processing, transformation, and scripting

• Familiarity with data orchestration and workflow automation (e.g., Apache Airflow, Cloud Composer)

• Experience with data ingestion, transformation, and loading (ETL/ELT) in cloud environments

• Knowledge of data governance, data quality, privacy, and security best practices

• Proficient in version control systems (Git) and collaboration tools (e.g., GitHub, GitLab)

• Understanding of SDLC/Agile methodologies and working in cross-functional teams

Preferred Skills

• Experience with additional cloud services (AWS, Azure) and multi-cloud data strategies

• Data warehousing concepts and experience with star/snowflake schema design

• Experience with data lake architectures and tools (e.g., Cloud Storage lifecycle, data cataloging)

• Knowledge of data visualization or reporting integrations to business stakeholders

• Familiarity with containerization (Docker) and orchestration (Kubernetes) for data services

• Experience with data security tooling and IAM configurations in cloud environments

Overall Responsibilities

• Design, implement, and optimize scalable data pipelines and data models on GCP

• Collaborate with data engineers, data scientists, analysts, and business stakeholders to translate requirements into robust data solutions

• Develop and maintain data ingestion, transformation, and loading processes, ensuring data quality and accuracy

• Build data models and schemas suitable for analytics, BI, and reporting

• Implement data governance, lineage, and security controls across cloud data platforms

• Monitor, profile, and optimize data workflows for performance, cost, and reliability

• Develop documentation, runbooks, and architecture diagrams for data pipelines and platforms

• Stay current with evolving data technologies and best practices; advocate for continuous improvement

• Work with cross-functional teams to ensure alignment with enterprise data strategy and regulatory requirements

Technical Skills (By Category)

Programming Languages (Essential & Preferred)

• Essential: Python or Java (for data processing and orchestration tasks)

• Preferred: SQL, Scala, or other data-focused languages for specialized workloads

Databases/Data Management

• Essential: SQL-based data modeling; experience with relational data stores (BigQuery, PostgreSQL, MySQL, etc.)

• Preferred: NoSQL databases (e.g., MongoDB, Cassandra); data warehousing concepts; data governance and lineage

Cloud Technologies

• Essential: Proficiency with GCP data services (BigQuery, Dataflow/Apache Beam, Cloud Storage, Pub/Sub)

• Preferred: Experience with multi-cloud data strategies (AWS, Azure), and cloud security basics

Frameworks and Libraries

• Essential: Data processing frameworks (Pandas/NumPy in Python; equivalent in Java), data orchestration libraries

• Preferred: Spark/Databricks, Dask, data cataloging and governance tools

Development Tools and Methodologies

• Essential: Git-based version control; Agile/Scrum practices; ETL/ELT tooling familiarity

• Preferred: Infra as Code (Terraform), CI/CD integration for data solutions, testing frameworks

Security Protocols

• Essential: Data privacy, secure data handling, and access controls in cloud environments

• Preferred: Data encryption, IAM best practices, data masking, and compliance standards (e.g., GDPR/CCPA)

Experience Requirements

• 8 to 10 years of hands-on data engineering experience with a focus on cloud data platforms

• Experience designing and operating data pipelines in GCP; familiarity with data warehousing and analytics

• Domain experience in finance, healthcare, or other data-intensive industries is a plus

• Demonstrated ability to collaborate with cross-functional teams and deliver end-to-end data solutions

• Alternative pathways: strong project portfolio, relevant certifications, or hands-on multi-cloud data engineering roles

Day-to-Day Activities

• Design, develop, and optimize data pipelines and models on the cloud

• Collaborate with stakeholders to define data requirements and translate them into technical designs

• Implement and monitor data quality, governance, and security controls

• Tune performance and manage costs of data workloads in the cloud

• Maintain documentation, runbooks, and architecture diagrams

• Participate in planning, stand-ups, reviews, and milestone reporting

• Mentor junior team members and share best practices

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field

• Relevant certifications in data engineering, cloud platforms (GCP preferred), or data governance are advantageous

• Demonstrated commitment to ongoing professional development in data engineering and cloud technologies

Professional Competencies

• Critical thinking and problem-solving abilities for complex data problems

• Clear communication and stakeholder management across technical and business teams

• Collaboration and leadership skills to guide cross-functional teams

• Adaptability to evolving data technologies and regulatory requirements

• Innovation mindset with a focus on scalable, secure, and maintainable data solutions

• Time management and prioritization in dynamic environments

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