Data Engineer

About Us

ADA is a data and artificial intelligence company that designs and executes integrated digital, analytics and marketing solutions . Operating across 12 markets in Asia Pacific, ADA partners with leading brands to drive their digital and data maturity and achieve their business goals.

WHY ARE WE HIRING

Following substantial growth in the last couple of years, ADA is growing in the ecommerce space to allow us to offer personalized end to end ecommerce solution . This is an exciting opportunity for someone to be a part of global team working across various clients in ecommerce space in almost all industry verticals.

ADA has a vision to create a unique take on end-to-end branded commerce. We establish and grow a brand's digital presence on eCommerce platforms through excellent marketing, content, and operations. We help customers own a fully customised web store with a stand-alone brand.com. From store build to web integration and customer service — we manage brands’ end-to-end processes so they can focus on things that matter.

KEY DUTIES

• Design, develop, and maintain scalable data pipelines and ETL processes to extract, transform, and load large volumes of structured and unstructured data from diverse sources in Batch and Real-time processing.
• Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand data requirements and translate them into technical solutions.
• Build and optimize data models, databases, and data warehouses for efficient storage, retrieval, and analysis of data.
• Implement data quality checks, validation rules, and monitoring systems to ensure the accuracy, completeness, and reliability of data.
• Develop and maintain documentation, standards, and best practices for data engineering processes and workflows.
• Stay abreast of emerging technologies and trends in data engineering, big data, and cloud computing to drive continuous improvement and innovation.
• Provide technical guidance and mentorship to junior team members, and actively participate in code reviews and knowledge sharing sessions.
  
  

Experience Needed

• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• 4-5 years of professional experience as a Data Engineer or similar role, with a strong focus on building data pipelines (both batch and real-time), ETL processes, and data infrastructure.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with data processing frameworks/libraries such as Apache Spark, Apache Kafka, and Hadoop.
• Solid understanding of relational and NoSQL databases, data modeling concepts, and SQL query optimization techniques.
• Hands-on experience with any cloud platforms such as AWS, Azure, or GCP, and familiarity with services like Databricks platfrom,AWS Glue, Azure Data Factory, or Google DataProc .
• Strong analytical and problem-solving skills, with the ability to troubleshoot complex data issues and performance bottlenecks.
• Experience with DevOps practices, version control systems (e.g., Git), and CI/CD pipelines with Jenkins.
• Experience with Airflow, NiFi or any other orchestration tool