Lead Cloud 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 yoy) 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 a highly accomplished and visionary Lead Cloud Data Engineer to lead our data engineering efforts shape our data infrastructure strategy and drive innovation within our organization. As a Lead Cloud Data Engineer you will leverage your extensive experience to design build and optimize complex data solutions in the cloud. You will lead a team of data engineers collaborate with crossfunctional teams and play a pivotal role in transforming our data landscape. If you are a dynamic leader with a strong background in data engineering cloud technologies and programming excellence we invite you to apply for this leadership position.

Responsibilities

1. Data Strategy: Develop and execute a forwardthinking data strategy encompassing data architecture technology stack and best practices to support business goals.
   
2. Team Leadership: Lead and mentor a team of data engineers fostering a culture of innovation collaboration and continuous learning.
   
3. Data Pipeline Excellence: Oversee the design development and maintenance of enterpriselevel data pipelines ensuring scalability reliability and performance.
   
4. Advanced Data Transformation: Utilize your expertise in Python and/or PySpark to architect and implement complex data transformations optimizations and ETL processes.
   
5. Data Governance and Compliance: Establish and enforce data governance standards ensuring data quality security lineage and compliance with industry regulations.
   
6. CrossFunctional Collaboration: Collaborate closely with data scientists analysts and stakeholders to understand complex data requirements and deliver tailored data solutions.
   
7. Documentation and Best Practices: Promote best practices in data engineering and maintain comprehensive documentation of data pipelines and processes.
   
8. Security and Scalability: Implement robust security measures and strategies for data scalability within cloud environments.
   

Preferred Skills

• DBT (Data Build Tool): Extensive experience with DBT for orchestrating and managing data transformations.
  
• Containerization and Orchestration: Proficiency in containerization and orchestration tools (e.g. Docker Kubernetes) for efficient deployment and scalability.
  
• Data Streaming: Knowledge of data streaming technologies (e.g. Kafka Apache Spark Streaming) for realtime data processing.
  
• Workflow Management: Familiarity with data orchestration and workflow management tools (e.g. Apache Airflow) for scheduling and automation.
  
• Cloud Certification: Relevant cloud certifications (e.g. AWS Certified Data Analytics Azure Data Engineer) demonstrating your expertise in cloud platforms.
  

Qualifications

• Bachelor s degree in computer science Information Technology or a related field (master s degree preferred).
  
• Minimum 8 years of relevant experience.
  
• Extensive experience in data engineering with a strong focus on cloudbased solutions.
  
• Proven leadership experience including managing and mentoring data engineering teams.
  
• Expertise in Python and/or PySpark for advanced data processing transformation and ETL tasks.
  
• Deep understanding of cloud platforms such as AWS Azure or Google Cloud.
  
• Advanced knowledge of data warehousing concepts and technologies (e.g. Redshift BigQuery).
  
• Exceptional problemsolving skills and attention to detail.
  
• Outstanding communication and leadership abilities with a strategic mindset.
  

Join our team and lead our data engineering efforts driving innovation and excellence in a dynamic environment. If you are an experienced Lead Cloud Data Engineer with a vision for data transformation we look forward to receiving your application!