Back
Tier-1 brand, mid-level generalist data engineer, and metro Bengaluru increase candidate competition.
Skills transfer across industries but require specific cloud, Snowflake and Spark expertise, so sensitivity is medium.
Explicit 4–8 years plus extensive mandatory AWS/Snowflake/Spark/ETL stack makes filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Architect and deliver scalable cloud-based data engineering solutions on AWS, including Enterprise Data Lake and Data hub projects.
Mentor junior developers and drive continuous improvement in data engineering practices within an agile team.
Collaborate with cross-functional teams to translate complex technical requirements into robust, secure data pipelines and cloud infrastructure.
4-8 years of hands-on experience in data engineering with focus on AWS cloud technologies.
Bachelor's degree required; Computer Science or related field preferred.
Strong expertise in AWS services including EMR, Glue, Sagemaker, S3, Redshift, DynamoDB, and streaming services (Kinesis, SQS, MSK).
Proficiency in Python or Java, Spark (core, SQL, streaming), Hadoop, Snowflake utilities, ETL pipelines, and data security/access controls.
Experienced in architecting and implementing enterprise-scale cloud data solutions with demonstrable AWS technical leadership.
Capable of mentoring junior team members and navigating complex technical challenges in fast-paced, agile environments.
Proficient in advanced big data tools and frameworks (Spark, Hadoop, Snowflake) with strong analytical and problem-solving skills.