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Job Role: Senior Data Engineer- Implementation & Modernization
Location: Hyderabad (Hybrid)
Exp: 5 Years+ (Relevant)
Early Joiners Preferred
Job Role Summary
The Data Engineer is responsible for building and optimizing high-performance, large-scaled data solutions on modern cloud platformsfrom the ground up. This role focuses on developing data engineering pipelines, working closely with the Cloud Solution Architects who defines overall architectural design. The Data Engineer is expected to deeply understand approved solution designs, data architectures, and modeling patterns to translate them into efficient and secure data pipelines. The ideal candidate brings strong SQL and Python skills, strong collaboration skills, and must be able to integrate solutions with a variety of technologies. The data engineer should be self-driven, able to work with minimum supervision and have extensive experience in Data Modeling, Data Warehousing, and ETL processing in a cloud environment.
Duties & Responsibilities
Qualifications
Required
Preferred qualifications
Job ID: 151906117
Skills:
snowflake , Data Management, Hadoop, Performance Tuning, Data Modeling, Dimensional Modeling, Redshift, Sql, Data Quality, Hive, Spark, Data Integration, Python, Airflow, big data systems, data warehouse scaling, ETL pipelines
Skills:
data engineering , snowflake , Pyspark, Scala, PostgreSQL, Kafka, Microsoft Sql Server, Bash, Kotlin, Redshift, Numpy, Pandas, Gcp, Kinesis, Linux, MySQL, Databricks, Azure, Python, AWS, Go, Dask
Skills:
Pyspark, Data Modeling, ELT, Cloud Storage, Numpy, Docker, Terraform, Python, BigQuery, Sql, Jenkins, Pandas, Spark, Kubernetes, Etl, GCP Core Services, Infrastructure as Code, Cloud Dataflow, Real-time streaming architectures, CI CD, Pub Sub, Cloud Run, GitHub Actions, API integrations, Cloud Functions, Cloud Dataproc, Cloud Composer Airflow
Skills:
data engineering , snowflake , Data Management, Hadoop, Performance Tuning, Dimensional Modeling, Data Modeling, Redshift, Sql, Data Quality, Hive, Spark, Data Integration, Python, Airflow, big data systems, data warehouse scaling, ETL pipelines
Skills:
Spark SQL, Distributed Computing, Metadata Management, Pyspark, Data Warehousing, Apache Spark, Kafka, Sql, Data Quality, Git, Kinesis, Databricks, Data Integration, Python, AWS, CI CD, streaming technologies, lakehouse architecture, access controls, Delta Lake, lineage governance, Databricks Workflows