Overview
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
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.
- Experience: Minimum of 10 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.
- 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).
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