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Tier-1 brand, mid-level data role, and metro Bangalore increase candidate competition.
Core data engineering skills are broadly transferable across industries.
Many mandatory technologies and explicit 5-8 years requirement raise shortlisting strictness.
Design and build data infrastructure and pipelines leveraging big data and cloud technologies to enable efficient data processing and analysis.
Develop and implement data integration and transformation solutions using tools like Spark, Kafka, Airflow, DBT, Flink, and Apache Iceberg.
Contribute to delivering actionable business insights by working with cloud platforms such as AWS and Azure and integrating technologies like Snowflake and CI/CD frameworks.
5-8 years of work experience in data engineering or related roles.
Mandatory technical skills include Big Data technologies, AWS, SQL, Spark, Python/Scala, S3, Glue, EMR, Aurora Postgres, Lambda, Kinesis, Kafka, Airflow, DBT, Flink, Apache Iceberg, Datadog.
Educational qualification: Bachelor of Technology or equivalent (B.Tech / M.Tech / M.E / MCA / B.E).
Work Experience Required: 5-8 years. Notice period: Not explicitly mentioned in the JD.
Experienced in architecting and developing scalable data pipelines and infrastructure using a mix of cloud (AWS, Azure) and big data tools.
Proficient in programming with Scala and/or Python and capable of integrating modern data engineering frameworks and CI/CD processes.
Familiar with enterprise data architecture principles and capable of leveraging advanced data processing tools to deliver business insights in a consulting or advisory environment.