Chief Data Engineer

We are a leading-edge technology company specializing in data-driven solutions to maximize business value for enterprises and brands.

Our comprehensive suite of work encompasses extraction, transformation, visualization, and analysis of data delivered through innovative products, services, and solutions.

We have developed a cutting-edge ETL tool, Daton, which serves as the backbone of our data engineering capabilities. Furthermore, we are now venturing into creating user-friendly data visualization solutions built on top of Daton.

We boast a world-class data team that excels at deciphering complex data insights and effectively communicating them to CXOs, thereby driving significant value creation.

We operate as a profitable and fast-growing startup with old-school values. Our presence in the intersection of data analytics and e-commerce positions us favorably amidst challenging market conditions.

In an era marked by economic headwinds forcing companies to downsize, outsource, and offshore, we leverage these tailwinds to propel our growth.

We prioritize talent and foster a culture that values employee well-being and growth. Our leadership team plays a critical role in designing, implementing, and optimizing data pipelines, leveraging expertise in programming, cloud platforms, and modern data warehousing solutions.

Data Pipeline Architecture:

Lead the design and architecture of scalable and efficient data pipelines to ensure optimal performance and reliability.

Programming and Scripting:

Utilize strong programming skills, particularly in languages like Python, to develop 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 to ensure 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.

We collaborate closely with cross-functional teams to provide technical leadership and guidance to junior data engineers.

We work hand-in-hand with data scientists, analysts, and business stakeholders to comprehend requirements and deliver impactful data solutions.

Quality Assurance:

Implement comprehensive data quality checks and validation processes to guarantee the accuracy and completeness of data.

Create and maintain detailed documentation for data engineering processes, data models, and cloud configurations.

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.

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.