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PwC brand, Bangalore metro, mid-level (5-8yrs), and broad multi-tech requirements increase applicant competition.
Core data engineering skills are highly transferable across industries.
Explicit 5-8 years plus many mandatory technologies implies high shortlisting strictness.
Design and develop robust data infrastructure and pipeline solutions using big data and cloud technologies for efficient data processing and analysis.
Leverage tools such as Spark, Scala/Python, Kafka, Airflow, DBT, Flink, and AWS managed services to enable data integration and transformation.
Contribute to client projects within Data and Analytics advisory to support actionable insights and business growth.
5-8 years of relevant work experience in data engineering or analytics roles.
Bachelor's degree required; B.Tech / M.Tech / M.E / MCA / B.E preferred in relevant fields.
Mandatory skills: Big Data, AWS, SQL, Python/Scala, Spark, S3, Glue, EMR, Aurora Postgres, Lambda, Kinesis, Kafka, Airflow, DBT, Flink, Apache Iceberg, Datadog.
Experience with Microsoft Azure is required; experience with Snowflake and CI/CD frameworks (e.g. Github) is a significant plus.
Experienced data engineer with strong hands-on skills in both cloud (AWS and Azure) and big data ecosystems.
Proficient in end-to-end data pipeline development and orchestration using modern technologies and frameworks relevant to Data & Analytics advisory.
Comfortable working with diverse technologies and tools to deliver integrated data solutions at enterprise scale.