Senior Data Engineer

Weekday AI (YC W21)

6 years

0 Lacs

chennai tamil nadu india

Posted:1 day ago| Platform:

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Skills Required

data support engineering relational mysql postgresql nosql mongodb redshift processing kafka etl integration pipeline programming python java scala apache spark analytics aws gcp azure communication collaboration design consistency integrity

Work Mode

On-site

Job Type

Full Time

Job Description

This role is for one of Weekday's clientsMin Experience: 6 yearsLocation: ChennaiJobType: full-time

Requirements

We are looking for a highly skilled and motivated

Senior Data Engineer

to join our clients team. You will play a key role in designing, implementing, and optimizing data architectures and pipelines to support scalable data solutions for our business.

Qualifications:

6-9 years of experience in data engineering, with a focus on building and managing data pipelines
Strong proficiency in relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra)
Experience in building data pipelines with data warehouses like Snowflake, Redshift
Experience in processing unstructured data stored from S3 using Athena, Glue etc
Hands-on experience with Kafka for real-time data streaming and messaging
Solid understanding of ETL processes, data integration, and data pipeline optimization
Proficiency in programming languages like Python, Java, or Scala for data processing
Experience with Apache Spark for big data processing and analytics is an advantage
Familiarity with cloud platforms like AWS, GCP, or Azure for data infrastructure is a plus
Excellent problem-solving skills and attention to detail
Strong communication and collaboration skills, with the ability to work effectively in a team environment

Key Responsibilities:

Design, build, and maintain efficient and scalable data pipelines to support data integration and transformation across various sources
Work with relational databases (e.g., MySQL, PostgreSQL, etc.) and NoSQL databases (e.g., MongoDB, Cassandra, etc.) to manage and optimize large datasets
Utilize Apache Spark for distributed data processing and real-time analytics
Implement and manage Kafka for data streaming and real-time data integration between systems. Collaborate with cross-functional teams to gather and translate business requirements into technical solutions
Monitor and optimize the performance of data pipelines and architectures, ensuring high availability and reliability
Ensure data quality, consistency, and integrity across all systems
Stay up-to-date with the latest trends and best practices in data engineering and big data technologies

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