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The ideal candidate will have strong experience in data engineering, cloud technologies, and software development, with a passion for building reliable, scalable, and secure data solutions.
Required technical expertise includes:
- Strong proficiency in SQL, Python, and Java.
- Hands-on experience designing, developing, and deploying cloud-based data pipelines using Google Cloud Platform (GCP), including BigQuery, Dataflow, and Dataproc.
- Experience with relational databases such as PostgreSQL and MySQL, as well as NoSQL and columnar databases.
- Understanding of Service-Oriented Architecture (SOA) and microservices-based solutions.
- Knowledge of data governance, security controls, encryption, and data masking techniques.
- Experience implementing CI/CD pipelines and Infrastructure as Code (IaC) using tools such as Terraform and Tekton.
- Ability to monitor, troubleshoot, and optimize cloud workloads for performance, scalability, and cost efficiency.
- Strong analytical, problem-solving, and communication skills.

Data Pipeline Architect & Builder: Spearhead the design, development, and maintenance of scalable data ingestion and curation pipelines from diverse sources. Ensure data is standardized, high-quality, and optimized for analytical use. Leverage cutting-edge tools and technologies, including Python, SQL, and DBT/Dataform, to build robust and efficient data pipelines.
End-to-End Integration Expert: Utilize your full-stack skills to contribute to seamless end-to-end development, ensuring smooth and reliable data flow from source to insight.
GCP Data Solutions Leader: Leverage your deep expertise in GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that not only meet but exceed business needs and expectations.
Data Governance & Security Champion: Implement and manage robust data governance policies, access controls, and security best practices, fully utilizing GCP's native security features to protect sensitive data.
Data Workflow Orchestrator: Employ Astronomer and Terraform for efficient data workflow management and cloud infrastructure provisioning, championing best practices in Infrastructure as Code (IaC).
Performance Optimization Driver: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions, ensuring optimal resource utilization and cost-effectiveness.
Collaborative Innovator: Collaborate effectively with data architects, application architects, service owners, and cross-functional teams to define and promote best practices, design patterns, and frameworks for cloud data engineering.
Automation & Reliability Advocate: Proactively automate data platform processes to enhance reliability, improve data quality, minimize manual intervention, and drive operational efficiency.
Effective Communicator: Clearly and transparently communicate complex technical decisions to both technical and non-technical stakeholders, fostering understanding and alignment.
Continuous Learner: Stay ahead of the curve by continuously learning about industry trends and emerging technologies, proactively identifying opportunities to improve our data platform and enhance our capabilities.
Business Impact Translator: Translate complex business requirements into optimized data asset designs and efficient code, ensuring that our data solutions directly contribute to business goals.
Documentation & Knowledge Sharer: Develop comprehensive documentation for data engineering processes, promoting knowledge sharing, facilitating collaboration, and ensuring long-term system maintainability.

Required
- Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Analytics, Engineering, or a related field, or equivalent practical experience.
- 5 to 7 years of experience in Data Engineering or Software Engineering.
- Minimum 2 years of hands-on experience building and deploying cloud-based data platforms, preferably on Google Cloud Platform (GCP).
- Strong proficiency in SQL and Python.
- Experience with BigQuery, Dataflow, Dataproc, and cloud-based data processing technologies.
- Experience with Terraform, CI/CD pipelines, and automation frameworks.
- Knowledge of cloud security, data governance, and data quality best practices.
Preferred
- Experience with DBT, Dataform, or similar transformation frameworks.
- Experience with Apache Airflow or Astronomer.
- Experience designing microservices and API-based integrations.
- Exposure to FinOps practices and cloud cost optimization.
  
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Data Engineer