The Role
Lead enterprise data engineering initiatives, define data architecture, and build scalable cloud-native platforms and Lakehouse solutions. Lead engineering teams, cloud migrations, governance, quality, metadata, security, and operational excellence efforts. Review technical designs and code, translate business requirements into solutions, and champion CI/CD, Infrastructure as Code, automation, and DataOps. Mentor engineers and drive modernization across the software development lifecycle.
Summary Generated by Built In
Job Title: Senior Data Engineer
Experience: 6–12 Years
Location: Bengaluru
Notice Period: Immediate or 15days
Job Summary
We are seeking an experienced and visionary Lead Data Engineer to lead enterprise-scale data engineering initiatives and drive the design, implementation, and modernization of cloud-native data platforms. The ideal candidate will have extensive experience in defining enterprise data architecture, leading high-performing engineering teams, and delivering scalable data solutions using modern cloud technologies. This role requires strong technical leadership, architectural expertise, and the ability to collaborate with cross-functional teams and business stakeholders.
Key Responsibilities
- Define and implement enterprise data architecture aligned with business and technology strategies.
- Lead multiple data engineering teams across complex enterprise projects and cloud transformation initiatives.
- Design, build, and optimize scalable cloud-native data platforms and modern data ecosystems.
- Architect and implement Lakehouse solutions using industry best practices.
- Drive enterprise-wide data governance, data quality, metadata management, and security initiatives.
- Review solution architecture, technical designs, and code to ensure adherence to engineering standards and best practices.
- Collaborate with Solution Architects, Product Owners, Business Analysts, and stakeholders to translate business requirements into scalable technical solutions.
- Ensure platform reliability, scalability, performance, and operational excellence.
- Champion automation, CI/CD, Infrastructure as Code (IaC), and DataOps best practices.
- Mentor and coach data engineers, fostering technical excellence and continuous learning.
- Identify opportunities for process improvements and technology modernization.
- Provide technical leadership throughout the software development lifecycle, from design through deployment and support.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.
- 6–12 years of experience in Data Engineering, Data Platform Development, or Cloud Data Architecture.
- Proven experience leading enterprise-scale data engineering programs and cloud migration initiatives.
- Strong expertise in designing scalable, secure, and high-performance data platforms.
- Demonstrated experience leading and mentoring technical teams.
- Strong understanding of data modeling, data warehousing, Lakehouse architecture, and distributed data processing.
- Excellent analytical, problem-solving, and decision-making skills.
- Outstanding communication, stakeholder management, and client-facing skills.
Preferred Qualifications
- Experience with enterprise data governance frameworks and metadata management solutions.
- Knowledge of real-time streaming and event-driven architectures.
- Experience with Infrastructure as Code (Terraform), containerization, and orchestration technologies.
- Azure certifications or cloud architecture certifications are highly desirable.
- Familiarity with Agile, Scrum, and modern software engineering practices.
Requirements
Required Technical Skills
- Strong programming expertise in Python and Scala
- Extensive experience with Apache Spark
- Hands-on experience with Databricks
- Strong knowledge of Snowflake
- Experience with Apache Kafka and event-driven data architectures
- Deep expertise in Microsoft Azure cloud services
- Hands-on experience with:
Azure Data Factory (ADF)
Azure Synapse Analytics
Azure Data Lake Storage - Strong understanding of CI/CD pipelines and DevOps practices
- Experience implementing DataOps methodologies
- Knowledge of Terraform or other Infrastructure as Code (IaC) tools is highly preferred
Skills Required
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline
- 6-12 years of experience in data engineering, data platform development, or cloud data architecture
- Experience leading enterprise-scale data engineering programs and cloud migration initiatives
- Expertise designing scalable, secure, and high-performance data platforms
- Experience leading and mentoring technical teams
- Strong understanding of data modeling, data warehousing, Lakehouse architecture, and distributed data processing
- Strong programming expertise in Python and Scala
- Extensive experience with Apache Spark
- Hands-on experience with Databricks
- Strong knowledge of Snowflake
- Experience with Apache Kafka and event-driven data architectures
- Deep expertise in Microsoft Azure cloud services
- Hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake Storage
- Strong understanding of CI/CD pipelines and DevOps practices
- Experience implementing DataOps methodologies
- Experience with enterprise data governance frameworks and metadata management solutions
- Knowledge of real-time streaming and event-driven architectures
- Experience with Terraform, containerization, and orchestration technologies
- Azure or cloud architecture certifications
- Familiarity with Agile, Scrum, and modern software engineering practices
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The Company
What We Do
Evnek Technologies is a Bengaluru-based technology and IT consulting company that helps organizations modernize through agentic and generative AI, machine learning, cloud solutions, data engineering, DevOps, and software/API development. Its services include AI-driven business transformation, autonomous intelligent agents, cloud migration and management, enterprise data capabilities, and scalable product development, with a mission to improve operational efficiency and create lasting business impact.
