Data Engineer_Mumbai

Responsibilities:

• Architect and build scalable, resilient and cost-effective software to support complex data pipelines.
• The architecture has two facets: Storage and Compute. The Data Engineer is responsible for designing and maintaining the different tiers of the data storage, including (but not limited to) archival, long-term persistent storage, transactional and reporting storage.
• The Data Engineer is responsible for designing, implementing and maintaining various data pipelines such as self-service ingestion tools, exports to application-specific warehouses and indexing activities.
• The Data Engineer is responsible for data modeling, as well as designing, implementing and maintaining various data catalogs, to support data transformation and product requirements.
• Collaborate with Data Science to understand, translate, and integrate methodologies into engineering build pipelines.
• Partner with product owners to translate complex business requirements into technical solutions, imparting design and architecture guidance.
• Provide expert mentorship to project teams on technology strategy, cultivating advanced skill sets in software engineering and modern SDLC.
• Stay informed about the latest technologies and methodologies by participating in industry forums, having an active peer network, and engaging actively with customers.
• Cultivate a team environment focused on continuous learning, where innovative technologies are developed and refined through teamwork.

Qualifications

• A degree in Computer Science or related technical field.
• Strong Computer Science fundamentals3+ years of professional Database Development, with languages such as ANSI SQL, TSQL, PL/SQL, PLSQL, plus database design, normalization, server tuning, and query plan optimization3+ years Software Engineering experience with programming languages such as Java, Scala, Python and Unix Shell3+ years of professional DBA experience with large datastores including HA and DR planning and support.
• Understanding of File Systems
• Demonstrated understanding and experience with big data tools such as Kafka, Spark and Trino/Presto
• Experience configuring database replication (physical and/or logical)ETL experience (3rd party and proprietary)Experience with orchestration tools such as Airflow
• Comfortable with version control systems such as git
• A thirst for learning new Tech and keeping up with industry advances.
• Excellent communication and knowledge-sharing skills.
• Comfortable working with technical and non-technical teams.
• Strong debugging skills.
• Comfortable providing and receiving code review feedback.
• A positive attitude, adaptability, enthusiasm, and a growth mindset.

Nice to have:

• A personal technical blog
• A personal (Git) repository of side projects
• Participation in an open-source community

Preferred skills:

• Comfortable using Docker and Kubernetes for container management.
• DevOps experience deploying and tuning the applications you’ve built.
• Monitoring tools such as Datadog, Prometheus, Grafana, Cloudwatch.