Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, metro location, generalist data-engineer role with broad tech requirements increases applicant competition.
Core data engineering skills are broadly transferable across industries, though consulting experience slightly favors fit.
Explicit 5–8 year requirement and extensive mandatory tech stack imply high screening strictness.
Design and develop data infrastructure, including data pipelines, integration, and transformation solutions using big data and cloud technologies.
Leverage advanced technologies like Spark, Kafka, Airflow, DBT, and cloud services (AWS, Azure) to enable efficient data processing and analytics.
Contribute to delivering actionable insights from raw data to support informed decision-making and drive business growth.
5-8 years of relevant work experience in data engineering or analytics.
Mandatory technical skills include Big Data technologies, AWS cloud services, SQL, Spark, Python and/or Scala, Kafka, Airflow, DBT, and data pipeline tools.
Bachelor's degree in Technology (B.Tech, M.Tech, M.E, MCA, or B.E).
Experience with Microsoft Azure and preferred knowledge of Snowflake is advantageous.
Experienced professional proficient in big data ecosystems and cloud platforms focusing on scalable data engineering solutions.
Strong hands-on expertise in implementing and managing data pipelines with Spark, Kafka, and orchestration tools like Airflow in advisory or client-focused environments.
Capable of working within Agile frameworks and integrating CI/CD processes with code repository tools (e.g., GitHub) for data engineering projects.