Data Engineer

Job Description

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 6 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).