Key Functions:

• Designing data models – Create efficient and scalable data models to support analytical and operational needs.

• Data architecture – Designing and implementing data structures that meet data architecture standards and business needs.

• Data integration – Integrate data from various sources into the data lake • Data pipeline – Implement automation to streamline data ingestion, transformation, and loading processes

• Data quality – Implement data validation and quality checks across the data management pipeline

• Collaboration – Collaborate with business analysts, developers, and business to understand data requirements and provide them with the necessary data

Key Performance Indicators (KPIs):

• Data Quality – Produce and query data with high accuracy, completeness, consistency, and validity for usability in analysis and key decision-making.

• Data Processing Efficiency – Data processing should maximize compute, storage, and transfer to optimize cost and run-time.

• System Uptime – Minimize disruption and downtime to ensure availability of data solutions during working and operating hours.

• Time-to-Insight – Data for business insights must be delivered within a workable timeline to ensure relevance and value appreciation.  

• Bachelor's Degree in Computer Science, Software Engineering, Statistics or related field; Strong foundation in computer science principles, algorithms, software development methodologies, and data analysis.

• Relevant certification such as AWS Associate – Data Engineering, Snowflake SnowPro Associate and Core is a plus.

• Working experience in at least one, and ideally several, of: Python, Java, Scala, SQL.

• 3+ years of experience as a data engineer, data scientist, or SQL developer

• Expert knowledge of relational databases (RDBMS) – i.e. MySQL, PostgreSQL, MSSQL; knowledge in no-SQL databases (i.e Couchbase) is a plus.

• Working knowledge of data warehousing concepts and technologies (e.g., Snowflake, Redshift, BigQuery); proficiency in Snowflake is a plus.

• Working knowledge of cloud-based data services (e.g., AWS S3, Azure Blob Storage, Google Cloud Storage).

• Familiarity with data integration tools (e.g., Apache Airflow, Talend, Informatica)

• Proficient knowledge of data analysis concepts, Familiarity with data visualization tools (i.e. Tableau, Power BI) is a plus.

• Solid understanding of fundamental data structures

• Knowledge of data modeling and schema design

• Basic understanding of software development methodologies (e.g., Agile, Scrum)

• Strong analytical skills with the ability identify key business insights from aggregated and consolidated data. Soft Skills

• Excellent verbal and written communication skills, with the ability to collaborate across teams.

• Team player with a willingness to learn and work in an agile environment.

• Strong organizational and time management skills, with the ability to prioritize tasks effectively.