Senior Data Engineer - Python/Scala (5-10 yrs)

Job Description :

Key Responsibilities :

1. Data Solution Design and Development :

- Architect, design, and implement end-to-end data pipelines and systems that handle largescale, complex datasets.

- Ensure optimal system architecture for performance, scalability, and reliability.

- Evaluate and integrate new technologies to enhance existing solutions.

- Implement best practices in ETL/ELT processes, data integration, and data warehousing.

2. Project Leadership and Delivery :

- Lead technical project execution, ensuring timelines and deliverables are met with high quality.

- Collaborate with cross-functional teams to align business goals with technical solutions.

- Act as the primary point of contact for clients, translating business requirements into actionable technical strategies.

3. Team Leadership and Development :

- Manage, mentor, and grow a team of 5 to 7 data engineers.

- Conduct code reviews, validations, and provide feedback to ensure adherence to technical standards.

- Provide technical guidance and foster an environment of continuous learning, innovation, and collaboration.

4. Optimization and Performance Tuning :

- Analyze and optimize existing data workflows for performance and cost-efficiency.

- Troubleshoot and resolve complex technical issues within data systems.

5. Adaptability and Innovation :

- Embrace a consulting mindset with the ability to quickly learn and adopt new tools, technologies, and frameworks.

- Identify opportunities for innovation and implement cutting-edge technologies in data engineering. '

- Exhibit a "figure it out" attitude, taking ownership and accountability for challenges and solutions.

6. Client Collaboration :

- Engage with stakeholders to understand requirements and ensure alignment throughout the project lifecycle.

- Present technical concepts and designs to both technical and non-technical audiences.

- Communicate effectively with stakeholders to ensure alignment on project goals, timelines, and deliverables.

7. Learning and Adaptability :

- Stay updated with emerging data technologies, frameworks, and tools.

- Actively explore and integrate new technologies to improve existing workflows and solutions.

8. Internal Initiatives and Eminence Building :

- Drive internal initiatives to improve processes, frameworks, and methodologies.

- Contribute to the organization's eminence by developing thought leadership, sharing best practices, and participating in knowledge-sharing activities.

Qualifications :

Education :

- Bachelor's or Master's degree in computer science, Data Engineering, or a related field.

- Certifications in cloud platforms such as Snowflake Snowpro, Azure Data Engineer is a plus.

Experience :

- 5 to 10 years of experience in data engineering with hands-on expertise in data pipeline development, architecture, and system optimization.

- Proven track record in leading data engineering teams and managing end-to-end project delivery.

Technical Skills :

- Expertise in programming languages such as Python, or Scala.

- Proficiency in designing and delivering data pipelines in Cloud Data Warehouses (e.g., Snowflake, Redshift), using various ETL/ELT tools such as Matillion, dbt, Striim, etc.

- Solid understanding of database systems (relational and NoSQL) and data modeling techniques.

- Hands-on experience of 2+ years in designing and developing data integration solutions using Matillion and/or dbt. o Strong knowledge of data engineering and integration frameworks.

- Expertise in architecting data solutions.

- Successfully implemented at least two end-to-end projects with multiple transformation layers.

- Good grasp of coding standards, with the ability to define standards and testing strategies for projects.

- Proficiency in working with cloud platforms (AWS, Azure, GCP) and associated data services.

- Enthusiastic about working in Agile methodology.

- Possess a comprehensive understanding of the DevOps process including GitHub integration and CI/CD pipelines.

- Experience working with containerization (Docker), and orchestration tools (such as Airflow, Control-M).

Soft Skills :

- Exceptional problem-solving and analytical skills.

- Strong communication and interpersonal skills to manage client relationships and team dynamics.

- Ability to thrive in a consulting environment, quickly adapting to new challenges and domains.

- Demonstrated accountability, ownership, and a proactive approach to solving problems.