Lead Data Engineer
2 weeks ago
About Saras Analytics: We are an ecommerce focused end to end data analytics firm assisting enterprises & brands in data driven decision making to maximize business value. Our suite of work spans extraction, transformation, visualization & analysis of data delivered via industry leading products, solutions & services. Our flagship product is Daton, an ETL tool. We have now ventured into building exciting ease of use data visualization solutions on top of Daton. And lastly, we have a world class data team which understands the story the numbers are telling and articulates the same to CXOs thereby creating value. Where we are Today: We are a boot strapped, profitable & fast growing (2x y-o-y) startup with old school value systems. We play in a very exciting space which is intersection of data analytics & ecommerce both of which are game changers. Today, the global economy faces headwinds forcing companies to downsize, outsource & offshore creating strong tail winds for us. We are an employee first company valuing talent & encouraging talent and live by those values at all stages of our work without comprising on the value we create for our customers. We strive to make Saras a career and not a job for talented folks who have chosen to work with us. The Role: We are seeking an accomplished Lead Data Engineer with strong programming skills, cloud expertise, and in-depth knowledge of Big Query/Snowflake data warehousing technologies. As a key leader in our data engineering team, you will play a critical role in designing, implementing, and optimizing data pipelines, leveraging your expertise in programming, cloud platforms, and modern data warehousing solutions. Responsibilities: Data Pipeline Architecture: Lead the design and architecture of scalable and efficient data pipelines, ensuring optimal performance and reliability. Programming and Scripting: Utilize strong programming skills, particularly in languages like Python, for developing robust and maintainable data engineering solutions. Cloud Platform Expertise: Apply extensive experience with cloud platforms (e.G., AWS, Azure, Google Cloud) to design, deploy, and optimize data engineering solutions in a cloud environment. BigQuery/Snowflake Knowledge: Demonstrate deep understanding and hands-on experience with BigQuery/Snowflake for efficient data storage, processing, and analysis. ETL Processes: Lead the development of Extract, Transform, Load (ETL) processes, ensuring seamless integration of data from various sources into the data warehouse. Data Modeling and Optimization: Design and implement effective data models to support ETL processes and ensure data integrity and efficiency. Collaboration and Leadership: Collaborate with cross-functional teams, providing technical leadership and guidance to junior data engineers. Work closely with data scientists, analysts, and business stakeholders to understand requirements and deliver effective data solutions. Quality Assurance: Implement comprehensive data quality checks and validation processes to ensure the accuracy and completeness of data. Documentation: Create and maintain detailed documentation for data engineering processes, data models, and cloud configurations. Technical Skills: Programming Languages: Expertise in programming languages, with a strong emphasis on Python. Cloud Platforms: Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud. Big Data Technologies: Proficiency in big data technologies and frameworks for distributed computing. Data Warehousing: In-depth knowledge of modern data warehousing solutions, with specific expertise in BigQuery/Snowflake. ETL Tools: Experience with ETL tools like Apache NiFi, Talend, or similar. SQL: Strong proficiency in writing and optimizing SQL queries for data extraction, transformation, and loading. Collaboration Tools: Experience using collaboration and project management tools for effective communication and project tracking. Soft Skills: Strong leadership and mentoring capabilities. Excellent communication and presentation skills. Strategic thinking and problem-solving abilities. Ability to work collaboratively in a cross-functional team environment. Educational Qualifications: Bachelor’s or Master’s degree in Computer Science Data Engineering, or a related field. Experience: 8+ years of experience in data engineering roles with a focus on programming, cloud platforms, and data warehousing. If you are an experienced Lead Data Engineer with a strong programming background, cloud expertise, and specific knowledge of BigQuery/Snowflake, we encourage you to apply. Please submit your resume and a cover letter highlighting your technical skills, leadership experience, and contributions to data engineering projects.
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Lead Data Engineer
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