KAS Services - Data Engineer

Minimum Requirements :

- Mandatory Formal Education/Qualifications e.g. CPA

- Bachelor's degree (Business / Engineering / Science / Finance / Economics / Statistics)

Essential Qualifications, Skills and Experience:

- Minimum 3+ years' experience in advanced SQL working knowledge and experience working with a variety of relational databases, SQL query authoring.

- 2+ years of experience in building data pipelines and data centric applications using distributed storage platforms like S3 and distributed processing platforms like Spark, Airflow, Kafka etc

- Minimum of 2+ experience in extract, transform, and load data from a wide variety of data sources using SQL (Snowflake, Oracle) and ability to use a major programming (e.g. Python /Java) and/or a scripting language (Perl, Unix shell) to process data for modelling.

- Deep working knowledge of AWS technologies such as S3, EC2, EMR, RDS, Lambda, Elasticsearch, Cloudformation, Cloudwatch etc.

- Advanced level working knowledge of Git and CI/CD pipeline technologies such as Jenkins, Chef, Kubernetes & Docker containers

- Development and implementations of data warehouses, data lake / reservoirs, business Intelligence, data modelling and large-scale data processing systems.

- Experience of working in an agile development model including continuous integration & continuous delivery (CI/CD).

Other Skills/Knowledge/Abilities/Technology Used:

To be successful in this role you will require the following attributes:

- Hands on and deep experience with schema design and dimensional data modelling

- Able to build processes that support data transformation, data structures, metadata, dependency and workload management.

- Experience with object-oriented/object function scripting languages: Python, Scala, Java etc

- Thorough knowledge of data warehouses, business Intelligence applications along with NoSQL databases and ETL technologies like Informaticaetc

- Expertise in different methodologies for data ingestion, transformation, virtualisation and building the data consumption model.

- Development and implementation of big data technologies and multiple scripting and languages (YAML, Python)..