Azure Data Architect

Azure Data Architect

Location: Cary, NC (Onsite)

Fulltime only (USC/GC/GCEAD)

• Collect, store, process and analyze large datasets to build and implement extract, transfer, load (ETL) processes.


• Develop reusable frameworks to reduce the development effort involved thereby ensuring cost savings for the projects.


• Develop quality code with thought through performance optimizations in place right at the development stage.


• Appetite to learn new technologies and be ready to work on new cutting-edge cloud technologies.


• Work with team spread across the globe in driving the delivery of projects and recommend development and performance improvements.

Essential Business Experience and Technical Skills:

• Building and Implementing data ingestion and curation process developed using Big data tools such as Spark (Scala/python/Java), Hive, HDFS, Sqoop, Kafka, Kerberos, Impala etc. and CDP 7.x


• Ingesting huge volumes data from various platforms for Analytics needs and writing high-performance, reliable, and maintainable ETL code Strong.


• Strong analytic skills related to working with unstructured datasets.


• Strong experience in building/designing Data warehouses, data stores for analytics consumption On prem and Cloud (real time as well as batch use cases).


• Ability to interact with business analysts and functional analysts in getting the requirements and implementing the ETL solutions.

Required:

• 8+ years of solutions development and delivery experience with 5+ years of recent experience in data engineering.


• Proficiency and extensive experience with Spark & Scala/Python and performance tuning.


• Hive database management and Performance tuning - Partitioning / Bucketing.


• Strong SQL knowledge and data analysis skills for data anomaly detection and data quality assurance.


• Very good problem solver and excellent communication skills - both written and verbal.

Preferred:

• Expertise in Python and experience writing Azure functions using Python/Node.js


• Experience using Event Hub for data integrations.


• Hands on expertise in: Implementing analytical data stores in Azure platform using ADLS/Azure data factory /Data Bricks and Cosmos DB (mongo/graph API).


• Experience ingesting using Azure data factory, Complex ETL using Data Bricks.


• Eagerness to learn new technologies on the fly and ship to production.