Data Engineer

We are seeking a highly skilled Senior Data Engineer to join our team. The ideal candidate will have extensive experience in designing and implementing scalable data solutions, working with large datasets, and building robust data pipelines and leveraging APIs. This role requires strong expertise in cloud platforms and a deep understanding of data engineering best practices within the e-commerce industry.

Education/ Experience:

• Bachelor's degree in Computer Science, Engineering, or related field

• Minimum of 8+ years of experience working in a large-scale organization

• Proven experience with AWS, Azure, and BigQuery for data storage and processing.

• Strong proficiency in SQL, Python, and data transformation tools is a must.

• Hands-on experience in building ETL pipelines, data orchestration frameworks, and RESTful APIs.

• Experience handling large-scale datasets and optimizing data workflows.

• Familiarity with e-commerce industry data, including web analytics and transactional data.

• Knowledge of data modeling, normalization, and aggregation techniques.

Skills and Ability:

• Experience with distributed systems and big data technologies (e.g., Spark, Redshift, Hadoop).
• Solid understanding of data governance, security, and compliance in cloud environments.
• Exposure to real-time data processing and streaming platforms (e.g., Kafka).

Work Conditions/ Physical Demands:

• This position is primarily performed in a home office or other approved remote work environment. The employee is expected to maintain a safe, secure, and distraction-free workspace with reliable internet access. Duties primarily involve prolonged periods of sitting, working on a computer, and communicating via phone and video conferencing.
• The employee must be able to frequently use a computer, keyboard, mouse, and other standard office equipment, as well as communicate effectively with colleagues, customers, and business partners. Occasional lifting of office materials or equipment up to 15 pounds may be required.

Travel:

• Travel is not required for this position (0%).

Pay & Benefits:

Compensation is determined by various factors such as location, education, knowledge, skills, competencies, and experience, as well as internal and external equity and organizational needs. Additionally, this role is eligible for an annual discretionary bonus.

The salary range for this position is $135,700 to $152,650 annually. The posted range reflects our national average range for the job. We may ultimately pay more or less than the published range based on the factors mentioned above. This range may be modified in the future.

At Liquidity Services, we provide a comprehensive benefits package that supports our employees'' well-being and provides growth opportunities and career development. Our offerings include:

• Competitive wages
• Healthcare (medical, dental, vision, prescription drugs, FSAs)
• 401(k) plan
• Paid time off (PTO) and holidays
• Paid parental leave
• Life and disability insurance
• Employee Assistance Program (EAP)
• Professional development and tuition assistance

Disclaimer: The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. Liquidity Services Inc. reserves the right to modify position duties at any time due to business necessity.

Liquidity Services is an Equal Opportunity Employer.

• Design, develop, and maintain data pipelines to process and transform large volumes of data efficiently.

• Normalize and aggregate data across multiple cloud platforms, including AWS, Azure, and Google BigQuery.

• Leverages APIs for data access and integration with internal and external systems

• Work with web and transactional data to support analytics and business intelligence initiatives.

• Ensure data quality, integrity, and security across all stages of the data lifecycle.

• Collaborate with cross-functional teams to understand data requirements and deliver scalable solutions.

• Optimize data workflows for performance and cost efficiency in cloud environments.

Required Qualifications & Skills

• Bachelor's degree in Computer Science, Engineering, or related field from a reputed institute in India.

• Minimum of 8+ years of experience working in a large-scale organization

• Proven experience with AWS, Azure, and BigQuery for data storage and processing.

• Strong proficiency in SQL, Python, and data transformation tools is a must.

• Hands-on experience in building ETL pipelines, data orchestration frameworks, and RESTful APIs.

• Experience handling large-scale datasets and optimizing data workflows.

• Familiarity with e-commerce industry data, including web analytics and transactional data.

• Knowledge of data modeling, normalization, and aggregation techniques.

• Design, develop, and maintain data pipelines to process and transform large volumes of data efficiently.

• Normalize and aggregate data across multiple cloud platforms, including AWS, Azure, and Google BigQuery.

• Leverages APIs for data access and integration with internal and external systems

• Work with web and transactional data to support analytics and business intelligence initiatives.

• Ensure data quality, integrity, and security across all stages of the data lifecycle.

• Collaborate with cross-functional teams to understand data requirements and deliver scalable solutions.

• Optimize data workflows for performance and cost efficiency in cloud environments.

Required Qualifications & Skills

• Bachelor's degree in Computer Science, Engineering, or related field from a reputed institute in India.

• Minimum of 8+ years of experience working in a large-scale organization

• Proven experience with AWS, Azure, and BigQuery for data storage and processing.

• Strong proficiency in SQL, Python, and data transformation tools is a must.

• Hands-on experience in building ETL pipelines, data orchestration frameworks, and RESTful APIs.

• Experience handling large-scale datasets and optimizing data workflows.

• Familiarity with e-commerce industry data, including web analytics and transactional data.

• Knowledge of data modeling, normalization, and aggregation techniques.