Cloud Data Engineer

1 week ago

New Delhi, India Bhavitha Tech, CMMi Level 3 Company Full time

We are seeking a talented and experienced Data Engineer with 3 -5 years experience to join our team, focusing on building and optimizing our data pipelines and architecture. The ideal candidate will be a hands-on contributor with a strong background in real-time data processing, modern data warehousing, and robust database design.Key Responsibilities ● Design, develop, and maintain scalable, high-performance ETL/ELT pipelines for both batch and real-time data processing. ● Implement and manage data solutions using Apache Flink for stream processing and low-latency data ingestion. ● Work extensively with Snowflake to manage and optimize our cloud data warehouse environment, focusing on cost-efficiency and query performance. ● Develop robust data models and schemas within StarRocks DB and other analytical stores to support business intelligence and reporting needs. ●Write clean, efficient, and well-tested code, primarily in Java, for data transformation and integration services. ● Ensure data quality, integrity, and compliance across all data assets. ● Collaborate with data scientists and analysts to implement and optimize models, including those related to statistical modeling and sampling. ● Monitor, troubleshoot, and optimize the data platform infrastructure and tools.Education & Experience ● Experience: 3 - 5 years of professional experience in a Data Engineering, Software Engineering, or similar role. ● Academic: Bachelor of Engineering or Master of Computer Applications in Computer Science, Information Technology, or a related quantitative field.Core Technical Skills ● Stream Processing: Deep expertise in Apache Flink (or similar technologies like Apache Kafka Streams/Spark Streaming). ● Programming: Strong proficiency in Java. Python is a significant plus. ● Data Warehousing: Hands-on experience with cloud data warehouses, specifically Snowflake. ● Databases: Expertise in analytical databases like StarRocks DB and strong familiarity with traditional relational (e.g., PostgreSQL, MySQL) and NoSQL databases. ● Data Fundamentals: Strong understanding of Data Engineering principles, including data modeling (e.g., Dimensional Modeling, Data Vault), schema design, and data governance.DesiredSkills and Tools ● Cloud Platforms: Experience with major cloud providers (AWS, Azure, or GCP) services relevant to data (e.g., S3/ADLS/GCS, EMR/Dataproc, Lambda/Cloud Functions). ● Data Orchestration: Proficiency with workflow management tools like Apache Airflow or similar (e.g., Dagster, Prefect). Big Data Ecosystem: Familiarity with the broader Apache ecosystem, particularly Apache Kafka for message queuing and Apache Spark (batch processing). ● Containerization: Working knowledge of Docker and Kubernetes for deploying and managing data services. ● DataOps/DevOps: Experience with CI/CD practices and tools (e.g., Git, Jenkins) applied to data pipelines. ● Data Governance & Quality: Understanding of tools and methods for metadata management, lineage tracking, and automated data quality checks (e.g., Great Expectations). ● Other Skillsets: Practical application of statistical modeling and sampling techniques in a data pipeline context.

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