Senior Data Engineer

Summary

Join BytePitch's growing data engineering team as a Senior Data Engineer. You will design, build, and maintain scalable data pipelines and infrastructure using AWS services, Snowflake, Python, and vector databases. Collaborate with data analysts and scientists to translate business needs into technical solutions. Automate data workflows, monitor pipeline health, and research new technologies. This role requires 3+ years of experience in data engineering, proficiency in Python and SQL, and hands-on AWS experience. BytePitch offers competitive salaries, additional benefits, fully remote work, flexibility, and a supportive, inclusive culture.

Requirements

• 3+ years of experience as a data engineer or in a similar data-focused role
• Proficient in Python and SQL, with experience in building data pipelines and ETL/ELT processes
• Hands-on experience with AWS services, including EC2, S3 and Glue
• Expertise in designing and working with data warehouses, such as Snowflake, Athena and Redshift
• Familiarity with vector databases and their applications in data-intensive use cases
• Strong problem-solving and analytical skills, with the ability to think critically and creatively
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams

Responsibilities

• Design and implement robust, fault-tolerant, and scalable data pipelines using a variety of technologies including AWS services, Snowflake, Python, and vector databases
• Develop and optimize data models, ETL/ELT processes, and data transformation logic to ensure high-quality, reliable, and performant analytics dashboards
• Collaborate with data analysts, data scientists, and business stakeholders to understand requirements and translate them into technical solutions
• Automate data ingestion, processing, and delivery workflows to improve efficiency and reduce manual effort
• Monitor data pipeline health, identify and resolve issues, and implement measures to ensure data integrity and availability
• Research and evaluate new data technologies, tools, and best practices to continuously improve our data engineering capabilities
• Contribute to the development of data engineering standards, guidelines, and documentation

Preferred Qualifications

• Master’s degree in Computer Science, Data Science, or a related field
• Experience with LLM embeddings
• Familiarity with cloud-native data engineering best practices and architectures
• Exposure to machine learning and data science workflows
• AWS certification

Benefits

• Two types of contracts are available: Employment & Service (B2B) Agreements
• Competitive salary according to your experience
• Additional benefits such as meal allowance, health insurance, extra days off (depending on the type of contract/location)
• Fully remote work
• Flexibility to help you balance the personal and professional aspects of your life
• An inclusive culture where you can be yourself and thrive professionally
• A supportive environment for your overall well-being
• A budget for training
• A personalised development plan based on our career paths
• Opportunities to travel according to the project/client needs
• Face-to-face company events per year to connect with colleagues and strengthen company culture