Experience:
- Minimum 10 years of experience in Data Engineering or related roles
- At least 2+ years in a Technical Lead (Data) capacity
- Note: This is not a management position — 100% hands-on capability required
Key Responsibilities
- Technically Lead and mentor a team of data engineers, fostering growth, collaboration, and technical excellence across project delivery.
- Architect, design, and implement scalable data pipelines and processing systems using modern cloud services (AWS, GCP, Azure).
- Establish and enforce data engineering best practices, standards, and governance frameworks.
- Collaborate with business stakeholders to understand data needs and deliver actionable, scalable solutions.
- Drive the technical vision and roadmap for data infrastructure and platforms.
- Optimize data workflows for performance, reliability, and cost efficiency.
- Provide technical leadership in data modeling and ETL/ELT design.
- Conduct code reviews, ensuring scalable and maintainable solutions.
- Support teams and stakeholders with data-related problem-solving.
- Communicate technical concepts effectively to technical and non-technical audiences.
- Design and lead discovery sessions with clients and internal teams for requirement gathering and architecture alignment.
- Automate and orchestrate complex data pipelines, reducing manual effort.
- Develop and maintain high-quality documentation of architectures, requirements, and processes.
- Support pre-sales engagements, including technical solutioning and proposal development.
- Create reusable frameworks and artifacts to accelerate delivery.
- Maintain relevant cloud certifications and contribute to thought leadership.
Technical Skills & Competencies
Programming & Querying Expertise
- Proficiency in Python and SQL is essential, with proven experience in developing scalable data solutions.
- Strong skills in writing clean, testable, and production-grade code for data transformation and orchestration.
- Experience with version control systems like Git and collaborative development practices.
- Familiarity with Scala or Java is a plus, particularly for big data processing frameworks.
Data Lake & Data Warehouse Expertise
- Proven experience in designing and implementing enterprise-grade data lake solutions.
- Hands-on experience with Cloud Data Engineering (AWS/GCP), Databricks, Delta Lake, and lakehouse architectures.
- Strong understanding of data warehouse concepts, including star and snowflake schemas.
- Expertise in query performance tuning, data partitioning, compression, and storage optimization.
- Understanding of data governance, access control, and security frameworks.
- Familiarity with medallion architecture or equivalent multi-tier data processing frameworks.
- Experience with real-time data streaming technologies such as Apache Kafka or AWS Kinesis.
Leadership & Soft Skills
- 2+ years of technical leadership experience.
- Demonstrated ability to mentor junior engineers and foster team capability growth.
- Excellent communication and collaboration skills across cross-functional teams.
- Strong problem-solving abilities, business acumen, and analytical thinking.
- Ability to manage multiple priorities in dynamic, fast-paced environments.
- Customer-focused mindset with strong stakeholder engagement skills.
- Experience in Agile methodologies and leading sprint planning and retrospectives.
Data Engineering Core Principles
- Expertise in data pipeline architectures, data integration patterns, and orchestration tools.
- Experience with data validation, testing frameworks, and data quality management.
- Knowledge of data privacy, compliance, and security best practices.
- Experience in connecting data pipelines to visualization layers for real-time analytics.
- Understanding of semantic layer design and self-service data modeling.
- Experience in end-to-end orchestration of pipelines from source systems to reporting tools.
- Proficiency in data modeling techniques and database design principles.
Industry Knowledge & Certifications
- Relevant cloud certifications (e.g., AWS Certified Data Analytics or Google Cloud Professional Data Engineer).
- Understanding of industry-specific data regulations (e.g., GDPR, CCPA, HIPAA) as applicable.
- Knowledge of emerging trends in data engineering, such as data mesh and data fabric architectures.
Ollion is an equal opportunity employer. We celebrate diversity and we are committed to creating an inclusive environment for all employees. Ollion does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, parental status, military service, or other non-merit factor.
Ollion is an equal opportunity employer. We celebrate diversity and we are committed to creating an inclusive environment for all employees. Ollion does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, parental status, military service, or other non-merit factor.
