Surge Global is a digital consultancy that leverages marketing, data, and technology to help businesses grow. As Sri Lanka’s leading digital firm, we employ the best content, creative, design & engineering talent the country has to offer.

Embracing a culture of transparency and equality in the workplace, we’ve built an environment helping Sri Lanka’s best marketing and creative talent thrive. Our team looks at untangling multivariate problems with an open mind and the willingness to constantly test and learn.

With our headquarters in Colombo Sri Lanka, we help scale startups to Fortune 500 companies across the United States, United Kingdom, Australia, and Sri Lanka.

Responsibilities:

• Collaborate with cross-functional teams to identify data requirements and design scalable data solutions.
• Develop, optimize, and maintain ETL pipelines to extract, transform, and load data from various sources into our data warehouse.
• Design and implement data models, ensuring data accuracy, consistency, and reliability.
• Performance-tune queries and processes to optimize data processing and ensure optimal system performance.
• Troubleshoot data-related issues, identify bottlenecks, and implement effective solutions.
• Stay up-to-date with the latest industry trends, technologies, and best practices in data engineering.
• Collaborate effectively within teams, contribute to planning discussions, and execute projects with precision.

Requirements:

• Bachelor's or higher degree in Computer Science, Engineering, or a related field.
• 4 Years experience with at least 2 years in the required fields
• Strong Hands on experience in below for at least 2 years
  • MS Data Stack SSIS / SQL / Azure
• Proven experience as a Data Engineer, with a focus on designing and building scalable data pipelines.
• Strong proficiency in programming languages such as Python, Java, or Scala.
• Expertise in working with SQL and NoSQL databases, data warehousing, and ETL processes.
• Hands-on experience with data modeling, data integration, and data architecture.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Excellent problem-solving and analytical skills.
• Strong communication and documentation skills.

Nice-to-Have:

• Experience with Big Data technologies like Hadoop, Spark, or Kafka.
• Familiarity with machine learning and data analytics concepts.