Lead Data Engineer

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:

1. Programming Languages: Expertise in programming languages, with a strong emphasis on Python.
2. Cloud Platforms: Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud.
3. Big Data Technologies: Proficiency in big data technologies and frameworks for distributed computing.
4. Data Warehousing: In-depth knowledge of modern data warehousing solutions, with specific expertise in BigQuery/Snowflake.
5. ETL Tools: Experience with ETL tools like Apache NiFi, Talend, or similar.
6. SQL: Strong proficiency in writing and optimizing SQL queries for data extraction, transformation, and loading.
7. 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.