Data Engineer+ GCP

Overall Responsibilities

• Design, develop, and maintain scalable data pipelines and workflows using GCP services
• Build and optimize data models, schemas, and warehouses (BigQuery, Cloud SQL, etc.) aligned with business needs
• Collaborate with data analysts, data scientists, and business stakeholders to gather requirements and deliver effective solutions
• Ensure data quality, security, and compliance across all data environments
• Automate data workflows, monitor system health, and troubleshoot issues proactively
• Optimize infrastructure for performance and cost-efficiency within GCP
• Document architecture, processes, and best practices for data engineering solutions
• Stay current with GCP advancements and incorporate new features and tools for continuous improvement

Software Requirements

• Proficiency in SQL and programming languages such as Python, Java, or Scala for data processing
• Hands-on experience with GCP data services including BigQuery, Cloud Dataflow, Cloud Data Fusion, Cloud Storage, and Dataproc
• Knowledge of ETL/ELT processes, data modeling, and data warehousing concepts
• Experience designing and implementing scalable and secure data pipelines on GCP
• Familiarity with containerization (Docker) and orchestration (GKE, Kubernetes)
• Understanding of data security, encryption, and compliance policies in cloud environments
• Experience with Apache Spark, Kafka, or Pub/Sub for real-time data streaming
• Knowledge of machine learning workflows on GCP (Vertex AI, AI Platform)
• Exposure to Cloud Identity & Access Management (IAM) and cybersecurity best practices

Category-wise Technical Skills Data Processing & Frameworks:

• GCP data services: BigQuery, Dataflow, Dataproc, Data Fusion, Cloud Storage
• Programming languages: Python, Java, Scala
• Real-time streaming: Pub/Sub, Kafka (preferred)
• Batch processing frameworks: Apache Spark, Dataflow

Cloud & Infrastructure:

• GCP Identity & Access Management (IAM), VPC, Cloud Networking
• Deployment automation: Terraform, Deployment Manager
• Container orchestration: Google Kubernetes Engine (GKE)

Data Modeling & Warehousing:

• Designing schemas and aggregations for analytical processing
• Data governance, access controls, lineage, and audit trails

Tools & Monitoring:

• Stackdriver, Data Studio, Looker, or Power BI for visualization and monitoring
• Version control: Git, CI/CD integrations

Experience

• 5+ years of experience in data engineering, data architecture, or related roles
• Proven track record deploying large-scale data pipelines on GCP
• Hands-on experience with enterprise data solutions, data lakes, or data warehouses
• Demonstrated ability to work collaboratively with cross-functional teams
• Experience with real-time data integration and processing workflows preferred

Day-to-Day Activities

• Design, develop, and maintain scalable data pipelines and workflows on GCP
• Implement, optimize, and troubleshoot batch and streaming data processes
• Collaborate with data analysts, scientists, and stakeholders to understand data requirements
• Monitor workflows, troubleshoot data pipeline issues, and implement improvements
• Ensure data security, privacy, and compliance across all environments
• Automate deployment and management of data infrastructure using DevOps tools
• Document technical architecture, processes, and standards
• Keep abreast of GCP innovations and incorporate relevant new features into solutions

Qualifications & Soft Skills Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field
• 5+ years of experience in data engineering, big data, or cloud data solutions
• Relevant certifications such as Google Professional Data Engineer are advantageous

Soft Skills:

• Strong analytical, problem-solving, and organizational skills
• Effective communication skills for collaborating with technical and non-technical teams
• Ability to work independently and as part of a team
• Detail-oriented, with a focus on quality and accuracy
• Adaptability and eagerness to learn emerging cloud and data technologies
• Proactive attitude with a focus on continuous improvemen 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