Data Modeler

Key Responsibilities:

• Design and implement scalable data architectures to support data storage, processing, and analytics.
• Design and implement data schemas within

  Snowflake

  to effectively support analytics, reporting needs.
• Establish and enforce data access roles and policies.
• Develop strategies to make data AI-ready, including data cleansing, transformation, and enrichment processes.
• Provide guidance and support for analytical development and modelling to enhance data visualization and reporting capabilities.
• Conduct performance tuning and optimization of data models to improve query efficiency and response times.
• Develop, maintain, and optimize ETL (Extract, Transform, Load) processes for Pacific Data Analytics Platform to ensure efficient data integration from various sources (Both internal and external datasets)
• Manage and optimize database / data warehouse systems such as snowflake ensuring high availability and performance.
• Analyze and tune database performance, identifying bottlenecks and implementing improvements to enhance query performance.
• Ensure data integrity, consistency, and accuracy through rigorous data quality checks and validations.
• Work closely with data engineers, application engineers, analysts, and other stakeholders to understand data needs and provide appropriate solutions.
• Leverage cloud technologies (mainly AWS) for data storage, processing, and analytics, ensuring cost-effectiveness and scalability.
• Document data processes, architectures, and workflows while establishing best practices for data management and engineering.
• Set up monitoring solutions to track data pipelines and database performance, ensuring timely maintenance and fault resolution.
• Ability to quickly analyze existing SQL code and make improvements to enhance performance, take advantage of new SQL features, close security gaps, and increase robustness and maintainability of the code.
• Implement data security measures and ensure compliance with relevant regulations regarding data protection and privacy.
• Provide guidance and mentorship to junior data engineers, fostering a culture of learning and continuous improvement.

Key Qualifications:

:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field with at least

  10+ years

  of software development experience
• Expert knowledge in Database like

  Oracle, PostgreSQL, SQL Server

  (preferably cloud hosted), with strong

  programming experience in SQL

  .
• Competence in data preparation and/or

  ETL

  tools like

  Snaplogic

  or

  Azure Data Factory

  or AWS Glue or SSIS (preferably strong working experience in one or more) to build and maintain data pipelines and flows.
• Programming language experience in

  Python, shells scripts

  (bash/zsh, grep/sed/awk etc..).
• Deep knowledge of

  databases

  ,

  stored procedures

  , optimizations of huge data
• In-depth knowledge of

  ingestion

  techniques, data cleaning, de-dupe, partitioning.
• Experience with building the infrastructure required for

  data ingestion and analytics

• Solid understanding of

  normalization and denormalization of data

  , database exception handling, transactions,

  profiling queries

  , performance counters, debugging, database & query optimization techniques
• Familiarity with

  SQL security techniques

  such as data encryption at the column level, Transparent Data Encryption (TDE), signed stored procedures, and assignment of user permissions
• Experience in understanding the source data from various platforms and mapping them into

  Entity Relationship Models (ER)

  for data integration and reporting
• Good understanding of

  Data

  Models, Data Architecture and Naming Conventions

• Knowledge of data visualization tools (e.g.,

  Tableau, Power BI

  ) is a plus.
• Exposure to Source control like

  GIT, Azure DevOps

• Understanding of

  Agile

  methodologies (Scrum, Kanban)
• Preferably experience with

  NoSQL

  database to migrate data into other type of databases with real time replication.
• Experience with CI/CD automation tools

Personal Strengths:

• Must have completed the certifications on Snowpro Advanced : Architect

• Very good communication skills.
• Ability to easily fit into a distributed development team.
• Ability to manage timelines of multiple initiatives.
• Ability to articulate insights from the data and help business teams make decisions
• Able to work with ambiguous requirements, to seek clarity around uncertainty and to manage risks
• Ability to communicate complex concepts to non-data audiences