Job Summary

Synechron is seeking an experienced Data Engineer supporting cloud-based big data solutions to design, build, and maintain scalable data pipelines and analytics infrastructure. This role focuses on leveraging Google Cloud Platform (GCP), Spark, Hive, and Python to deliver reliable, high-performance data workflows that support enterprise analytics, data migration, and operational excellence. The candidate will collaborate with cross-functional stakeholders to optimize data processing, ensure data quality, and support enterprise data strategies aligned with business objectives.

Software Requirements

Required Software Proficiency:

GCP services: BigQuery, Cloud Storage, Dataflow, or equivalent (latest version) — extensive experience supporting scalable data processing in cloud environments (supporting 6–8 years)
Apache Spark — strong hands-on experience supporting large-scale data processing and big data workflows (supporting 6+ years)
Hive — experience designing and managing data schemas and querying large datasets supporting data warehousing needs (supporting 5+ years)
Python — proficiency supporting data pipeline automation, scripting, and transformation (supporting 4+ years)
SQL (supporting databases like SQL Server, Oracle, PostgreSQL) — supporting data validation, migration, and operational reporting

Preferred Software Skills:

Cloud automation tools: Terraform, Dataflow, or Cloud Datafusion supporting environment automation (preferred)
Data orchestration tools: Apache Airflow or similar supporting pipeline scheduling and management (preferred)
Data visualization tools: Power BI, Tableau supporting reporting and dashboarding (preferred)

Overall Responsibilities

Design, develop, and optimize scalable data pipelines supporting enterprise analytics, data migration, and operational reporting within cloud environments
Build and maintain large-scale data ecosystems supporting real-time and batch data processing supporting business insights
Collaborate with data architects, data scientists, and business stakeholders to define requirements and translate them into efficient data workflows
Support cloud migration, schema design, and data validation activities ensuring compliance with governance and security standards
Monitor pipeline performance, troubleshoot failures, and optimize for data throughput and reliability
Automate data ingestion, transformation, and validation workflows supporting continuous integration and delivery processes
Support enterprise data strategy through schema management, data governance, and operational best practices
Document data architecture, pipeline design, operational procedures, and security policies supporting audits and compliance

Technical Skills (By Category)

Languages & Frameworks (Essential):

Python: supporting scripting, automation, and data transformation workflows
Spark, Hive supporting big data processing and large dataset management
SQL supporting data validation and query optimization in relational databases

Data & Warehouse Management:

Experience supporting data modeling, schema design, and data validation for data lakes/supporting large-scale data warehouses

Cloud & Infrastructure:

GCP supporting cloud-native data processing and migration (preferred)
Automation support via Terraform or cloud provider-specific automation tools (preferred)

Tools & Platforms:

Data orchestration: Apache Airflow or equivalent supporting scheduling workflows (preferred)
Visualization tools supporting operational dashboards and data reporting (preferred)

Experience Requirements

4+ years of supporting enterprise big data pipelines in cloud environments
Proven experience in designing, deploying, and optimizing data workflows supporting analytics and migration efforts
Extensive hands-on experience supporting data validation, reconciliation, and security in enterprise data ecosystems
Strong background supporting cloud migration, data lake/warehouse setup, and automation workflows (preferred)
Experience working with large datasets, optimizing queries, and ensuring high data throughput in cloud environments supporting enterprise operations

Day-to-Day Activities

Develop, test, and support scalable data pipelines supporting enterprise analytics and migration projects
Collaborate with data teams to refine data workflows, schemas, and pipeline performance
Support data migration, environment setup, and data validation activities supporting compliance and operational resilience
Troubleshoot pipeline failures, data quality issues, and performance bottlenecks supporting enterprise standards
Automate data ingestion, processing, and validation workflows using cloud-native tools and automation frameworks
Monitor data pipeline health, optimize throughput, and implement performance improvements supporting high-availability standards
Document data architecture, pipeline workflows, and operational procedures supporting audits and enterprise data governance

Qualifications

Bachelor's or Master's degree in Data Science, Computer Science, or related technical field
4+ years supporting large-scale, cloud-native data pipelines and enterprise analytics systems
Experience with cloud data platforms (preferably GCP) and supporting migration projects supporting enterprise resilience and compliance
Proficiency supporting data validation, reconciliation, and data governance within large operational environments
Certifications in cloud, big data, or data management (preferred) supporting data security and compliance requirements

Professional Competencies

Strong analytical and troubleshooting skills for complex data workflows and pipeline issues
Collaboration and stakeholder management capabilities supporting cross-functional teams
Ability to optimize data throughput, security, and operational efficiency supporting enterprise standards
Adaptability supporting evolving data standards, cloud platforms, and security regulations
Strategic mindset supporting scalable, secure, and compliant data ecosystems supporting business growth
Organizational skills for managing multiple pipelines, schema updates, and migration activities efficiently

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

Enterprise Data Engineer | Cloud Data Pipelines, GCP, Big Data, and Data Governance