Senior/Regular Data Engineer (Python, Spark, Hadoop) Offline

Project Description:

As a part of data migration into Azure Cloud - extract data from Oracle Hive cluster, convert into Parquet format and load to the Azure Blob Storage.

Utilize Spark for further data manipulations and analysis in a distributed manner.

Responsibilities:

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure 'big data' technologies;

• Implement data flows connecting operational systems, BI systems, and the big data platform;

• Build real-time, reliable, scalable, high-performing, distributed, fault tolerant systems;

• Clean and transform data into a usable state for analytics. Build data dictionary;

• Create data tools for analytics and data scientist team members that assist them in their ML endeavors;

• Design and develop code, scripts and data pipelines that leverage structured and unstructured data;

• Implement measures to address data privacy, security, compliance.

Mandatory Skills:

HiveQL, Scala, Java, Apache HBase, Python, Kafka Streams, Big Data, Apache Kafka, Hadoop

• Experience with designing data and analytics architectures in Microsoft Azure cloud;

• Experience with Big Data technologies like Spark, Hadoop, Hive, HBase, Kafka etc.;

• Fluency in several programming languages such as Python, Scala, Java, with the ability to pick up new languages and technologies quickly;

• Experience with data warehousing, data ingestion, and data profiling;

• Demonstrated teamwork, strong communication skills, and collaborative in complex engineering projects.

Nice-to-Have Skills:BS in computer science or related STEM field