Help move products through the development lifecycle from proofs of concept all the way to final, production-ready products Engineer, build and maintain scalable automated data pipelines. Implement best practices in management of data, including data processing, data quality and lineage. Managing code repositories, code deployments using GIT Automate, maintain and manage system, to ensure the availability, performance, scalability of product. Support regular and ad-hoc data querying and analysis. Qualifications: 3-5 years of experience in Python and data-focused packages, e.g., Pandas, Numpy; interacting with JSON, XML, CSV, TSV formatted data 3-5 years of experience with snowflake, SQL. 2-3 years of experience with DBT 2-3 years of experience with version control like git, bitbucket, and Linux environment Good to have knowledge of financial domain.

Description Job Description: We are looking for a highly skilled and motivated Data Engineer to join our team. This role is critical in designing, developing, and maintaining our data infrastructure to enable efficient data processing, analysis, and reporting. Your expertise in AWS, Snowflake, SQL, and Python will be essential in building and optimizing data pipelines, ensuring the scalability, reliability, and performance of our data ecosystem. Key Responsibilities: Collaborate with cross-functional teams to understand data requirements and develop effective data solutions. Design and implement scalable, high-performance data pipelines using Snowflake, SQL, and Python for ETL/ELT processes . Optimize data workflows for efficiency, reliability, and maintainability. Develop and maintain data models to ensure data accuracy, consistency, and integrity. Work with large structured and unstructured datasets to derive actionable insights. Identify and resolve data quality issues using data profiling, validation, and cleansing techniques. Monitor and troubleshoot data pipelines to ensure high availability and accuracy. Continuously improve data automation processes to streamline operations. Qualifications Requirements: Bachelor s degree in Computer Science, Information Technology, or a related field ( Master s preferred ). Strong experience with Snowflake for data warehousing and analytics. Proficiency in SQL for querying and manipulating data. Extensive experience in Python for building data pipelines and automation. Solid understanding of data modeling concepts and database design principles . Familiarity with ETL/ELT techniques, data integration, and transformation processes . Experience with version control systems (e.g., Git) and CI/CD pipelines is a plus. Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. Excellent communication skills to engage with both technical and non-technical stakeholders. Basic domain experience is a plus, particularly in understanding industry-specific data assets and developing testing plans accordingly. Preferred Skills: Experience with AWS services such as EC2, S3, CloudWatch, Lambda , etc. Proficiency in Linux scripting and automation using Bash Python . Hands-on experience with AWS CLI . Experience with CI/CD pipelines for data infrastructure deployment. Expertise in Snowflake, SQL, and Flyway for schema versioning and migration. Familiarity with data quality tools (e.g., Great Expectations ). Hands-on experience with ETL tools (e.g., Boomi ). Experience with batch processing tools like Apache Airflow .