DE&A - AIML - Data Science - Data Science Data Creation, Labeling and Model Evaluation

Job Description
About the Role
We are seeking a highly experienced and passionate Data Engineer to join our growing data team. As a Senior Data Engineer, you will be responsible for designing, developing, and maintaining our robust data infrastructure, ensuring data quality, availability, and scalability. You will play a critical role in empowering our data-driven decision-making by building and optimizing data pipelines, ETL processes, and data warehousing solutions. This is a senior-level position requiring extensive experience with database technologies, data modelling, and cloud platforms.

Responsibilities

• Data Pipeline Development & Maintenance: Design, build, and maintain end-to-end data pipelines for ingesting, processing, and transforming large datasets from various sources (e.g., relational databases, APIs, flat files, streaming data).
• ETL/ELT Process Optimization: Develop and optimize ETL/ELT processes using industry-standard tools and techniques, ensuring data accuracy, efficiency, and scalability.
• Database Design & Management: Design, implement, and manage relational databases, including schema design, indexing, performance tuning, and data governance.
• Data Warehousing: Design and implement data warehousing solutions to support business intelligence and reporting needs. Experience with star schema, snowflake schema, and other data modelling techniques is essential.
• Database Administration: Perform database administration tasks, including performance monitoring, capacity planning, backup and recovery, and security management.
• Data Quality & Governance: Implement data quality checks, validation rules, and data governance policies to ensure data accuracy and consistency.
• Cloud Platform Expertise: Leverage cloud platforms (e.g., AWS, Azure, GCP) for data storage, processing, and management.
• Collaboration & Communication: Collaborate with cross-functional teams (e.g., data scientists, business analysts, software engineers) to understand data requirements and deliver effective data solutions. Clearly communicate technical concepts to both technical and non-technical audiences.
• Mentoring & Knowledge Sharing: Mentor junior engineers and share knowledge and best practices within the team.
• Automation & Scripting: Automate data engineering tasks using scripting languages (e.g., Python, Bash).
• Stay Up to Date: Continuously research and evaluate new data technologies and techniques to improve our data infrastructure.
• Production Support: Monitoring the batch/jobs daily, no matter it's weekdays or weekend.
• Production Release: Actively participation in release process.

Qualifications

• Experience: Minimum of 8 years of experience as a Data Engineer or in a similar role.

• Database Expertise:

• Expert proficiency in SQL Server: Extensive experience with SQL Server, including database design, performance tuning, query optimization, and database administration.

• Expert proficiency in PostgreSQL: Deep understanding of PostgreSQL, including database design, performance tuning, query optimization, and database administration.

• Solid experience with other relational databases like MySQL, Oracle, etc. is a plus.

• ETL/ELT Tools: Proven experience with ETL/ELT tools (e.g., Apache Airflow, Informatica, Talend, SSIS, ADF etc.).

• Data Modelling: Strong understanding of data modelling principles and techniques (e.g., dimensional modelling, star schema, snowflake schema).
• Cloud Computing: Experience with cloud platforms (AWS, Azure, or GCP) and related data services (e.g., S3, Redshift, Snowflake, Azure Data Lake Storage).
• Programming & Scripting: Proficiency in scripting languages such as Python, Bash, or similar.
• Data Governance & Quality: Experience implementing data quality checks, data governance policies, and data validation rules.
• Problem-Solving & Analytical Skills: Excellent problem-solving and analytical skills with the ability to identify and resolve complex data-related issues.
• Communication & Collaboration: Excellent communication, collaboration, and interpersonal skills. Ability to work effectively in a team environment.
• Education: Bachelor's or master's degree in computer science, Information Technology, or a related field.

Bonus Points

• Experience with data streaming technologies (e.g., Kafka, Spark Streaming).
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
• Relevant certifications (e.g., AWS Certified Data Engineer, Microsoft Certified: Azure Data Engineer Associate).