Data Engineer

- 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.