Sr. Specialist - AZAY Data Engineering

Key Skills

Apache Airflow, Apache Cassandra, Apache Hadoop, Apache Hive, AWS, Azure, Cloud computing, Data Architecture, Data cleaning / Data cleansing, Data pipelines, Data Visualization, Data Warehousing, Debugging, Effective communication skills, Elasticsearch, English Proficiency, ETL frameworks, Github, GitLab, HBase, IBM Cognos, Luigi, MongoDB, PLSQL, Postgres, PowerBI, SAS, SDLC, Snowflake, SQL, T-SQL, Tableau

Job Description

Nice to know

Assist in delivering an improved version of the current Data Warehouse to serve latest business needs in the area of digital, data science and business intelligence. Support team lead to prioritize and design for a suitable solution but still serve a standard defined by Head of Data Office. Collaborate closely also with Data Governance to ensure data model is considered within our data storage, be it warehouses or lakes. Deliver on a committed timeline and agreed SLAs.

Your Day at Allianz Ayudhya

• Co-design enterprise level data warehouse and required Business Intelligence reports with the team manager. This may include data mart, staging database, or ETL extraction from multiple source systems.
• Develop data projects according to given priority, involving from understanding business requirements, to giving input to the design, development, unit test, automated test (if applicable) and manage the UAT process with users.
• Develop report/dashboard to support management/business unit by using Power BI, Cognos.
• Develop data pipelines by using PL/SQL, T-SQL or ETL tools (example: Data stage); transform data and/or to deliver management reports
• Performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Develop and enhance existing Data Mart in the data warehouse.
• Develop document relevant with internal process such as change request, ETL specification etc.
• Monitoring daily job, debug issues and providing maintenance support.

Must Have

• University degree in Computer Science, Information or Data Management
• Minimum 5 years experience in Data Architecture, Data Mart or Data Bank designs, Business Intelligence tools, Enterprise Data Warehouse or ETL tools
• Previous experience in Insurance and Finance is an advantage

Nice to Have

• Strong data transformation skills using T-SQL or PL/SQL. Experience with ETL tools is a plus.
• Technical expertise with package, procedures, functions, triggers and batch coding skills such as dynamic SQL, and parallel processing
• Ability to handle complex and large amounts of data transformation, mapping, migration, integration
• Experience of handling projects, from requirements stage to go-live. Able to communicate with users and IT infra team to drive the project delivery.
• Experience in Banking or Insurance is a plus but not compulsory.
• Technology expertise that is a plus: ETL (IBM Data Stage, MS SSIS, Data stage etc.) BI tools (Cognos, SAS Visual Analytics, Business Objects, Tableau, PowerBI)
• Knowledge of methodologies and processes for managing large scale databases, ETL processes, debugging, data management, integration, and transformation
• Understanding of data quality standards and data cleaning processes
• Experience with SDLC (software development life cycle) methodologies
• Knowledge of methodologies and processes for managing large scale databases, ETL processes, debugging, data management, integration, and transformation
• Understanding of ETL process and data warehousing concepts
• Relational databases, SQL and PSQL
• Big data technologies (Hadoop, Hive, HBase, Spark etc.)
• knowledge of version control systems (e.g. GitHub, GitLab etc.), data pipeline and workflow management tools (e.g. Airflow, Azkaban, Luigi, etc.)
• Experience with distributed databases and NoSQL databases like HBase, Elasticsearch, Postgres, Cassandra, MongoDB, Snowflake etc.
• Coordination and communication skills
• Good command of English (speaking, reading and writing)
• Knowledge of cloud computing (e.g. AWS, Azure)