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    Lead Data Architect - Hyderabad, India - Saras Analytics

    Saras Analytics
    Saras Analytics Hyderabad, India

    6 days ago

    Default job background
    Technology / Internet
    Description

    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 BigQuery/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.

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