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Siemens Healthcare

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4.3

based on 290 Reviews

Video summary

29 Siemens Healthcare Jobs

Data Engineer-Python,PySpark,SQL ,Spark Architecture,Azure Databricks

Siemens Healthcare

4.3

based on 290 Reviews

3-5 years

Bangalore / Bengaluru

1 vacancy

Data Engineer-Python,PySpark,SQL ,Spark Architecture,Azure Databricks

Siemens Healthcare

posted 8d ago

Job Role Insights

Flexible timing

Key skills for the job

Digital Marketing Python SQL Analytical Chemistry Informatica Apache Nifi

+ 2 more

Job Description

As a Data Engineer , you are required to:

Design, build, and maintain data pipelines that efficiently process and transport data from various sources to storage systems or processing environments while ensuring data integrity, consistency, and accuracy across the entire data pipeline.

Integrate data from different systems, often involving data cleaning, transformation (ETL), and validation. Design the structure of databases and data storage systems, including the design of schemas, tables, and relationships between datasets to enable efficient querying. Work closely with data scientists, analysts, and other stakeholders to understand their data needs and ensure that the data is structured in a way that makes it accessible and usable.

Stay up-to-date with the latest trends and technologies in the data engineering space, such as new data storage solutions, processing frameworks, and cloud technologies. Evaluate and implement new tools to improve data engineering processes.

Qualification : Bachelors or Masters in Computer Science Engineering, or equivalent. Professional Degree in Data Science, Engineering is desirable.

Experience level : At least 3 - 5 years hands-on experience in Data Engineering, ETL.

Desired Knowledge Experience :

Spark: Spark 3.x, RDD/DataFrames/SQL, Batch/Structured Streaming
- Knowing Spark internals: Catalyst/Tungsten/Photon
Databricks: Workflows, SQL Warehouses/Endpoints, DLT, Pipelines, Unity, Autoloader
IDE: IntelliJ/Pycharm, Git, Azure Devops, Github Copilot
Test: pytest, Great Expectations
CI/CD Yaml Azure Pipelines, Continuous Delivery, Acceptance Testing
Big Data Design: Lakehouse/Medallion Architecture, Parquet/Delta, Partitioning, Distribution, Data Skew, Compaction
Languages: Python/Functional Programming (FP)
SQL : TSQL/Spark SQL/HiveQL
Storage : Data Lake and Big Data Storage Design

additionally it is helpful to know basics of:

Data Pipelines : ADF/Synapse Pipelines/Oozie/Airflow
Languages: Scala, Java
NoSQL : Cosmos, Mongo, Cassandra
Cubes : SSAS (ROLAP, HOLAP, MOLAP), AAS, Tabular Model
SQL Server : TSQL, Stored Procedures
Hadoop : HDInsight / MapReduce / HDFS / YARN / Oozie / Hive / HBase / Ambari / Ranger / Atlas / Kafka
Data Catalog : Azure Purview, Apache Atlas, Informatica