Role : Google Data Engineer Developer/ Lead
Role Overview :
This pivotal role involves the end-to-end design, development, and optimization of robust data pipelines and scalable data solutions within the Google Cloud Platform (GCP) ecosystem. You will be instrumental in transforming raw data into actionable insights, working closely with cross-functional teams including data scientists, business analysts, and product managers. Your contributions will directly impact strategic decision-making, enhance operational efficiencies, and empower our business to leverage data as a core asset, driving innovation and delivering superior value to our customers.
Key Responsibilities :
- Architect and implement highly scalable and resilient data solutions on GCP, leveraging services like BigQuery, Cloud Dataflow, Cloud Storage, and Cloud Composer to meet evolving business intelligence and analytics needs.
- Develop, test, and deploy complex ETL/ELT processes to ingest, transform, and load large datasets from diverse sources, ensuring data quality, consistency, and timely availability for various stakeholders.
- Optimize existing data infrastructure and pipeline performance for efficiency, cost-effectiveness, and reliability, continuously seeking improvements in data processing and storage mechanisms.
- Collaborate effectively with data consumers, including data scientists and business users, to translate intricate data requirements into technical specifications and deliver robust data products that drive strategic outcomes.
- Provide technical leadership and mentorship to junior engineers, fostering best practices in data engineering, promoting code quality, and contributing to a culture of continuous learning and innovation within the team.
Required Skillset :
- Demonstrated deep expertise in Google Cloud Platform (GCP) data services, including advanced proficiency with BigQuery, Cloud Dataflow, Cloud Storage, and Cloud Composer for orchestration.
- Proven ability to design, build, and manage complex ETL/ELT pipelines for large-scale data processing and warehousing, ensuring data integrity and performance.
- Strong command of SQL and programming languages such as Python, applied effectively for data manipulation, automation, and API integration.
- Comprehensive understanding of data warehousing principles, dimensional modeling, and schema design best practices.
- Exceptional analytical and problem-solving capabilities, with a meticulous attention to detail in data validation and error handling.
- Excellent communication and interpersonal skills, enabling effective collaboration with both technical teams and non-technical business stakeholders.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative discipline.
- Adaptability to thrive in a dynamic, multi-location environment across Bangalore, Hyderabad, Chennai, Delhi, Pune, and Vishakhapatnam/Vizag, embracing hybrid or on-site work models as required.
Technical/Functional Skills :
- Google Cloud Platform : In-depth knowledge of GCP, including Cloud Dataflow, BigQuery, Cloud Storage, and Cloud Composer.
- Data Engineering : Strong understanding of data engineering concepts, including data modeling, ETL, and data warehousing.
- Expertise in Cloud storage, Dataproc, Cloud Functions, Messaging/Streaming (pub-sub)
- Programming : Proficiency in programming languages, including Python, Java, or SQL.
- Data Governance : Familiarity with data governance frameworks, including data quality, data security, and data compliance.
- Communication : Excellent communication and collaboration skills.
- Google Cloud Certifications : Relevant certifications, such as Google Cloud Certified - Professional Data Engineer or Google Cloud Certified - Enterprise Data Engineer.
- Big Data : Experience with big data technologies, including Hadoop, Spark, or NoSQL databases.
- Machine Learning : Experience with machine learning frameworks, including TensorFlow or Scikit-learn.
- Cloud Experience- : Experience with other cloud-based data platforms, including AWS or Azure
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