Lead Engineer - Data
New
J
JobgetherData Engineering
IndiaFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- Minimum of 10 years of experience in data engineering or related disciplines, including at least 2 years in a hands-on technical lead role.
- Required Skills
- AWSPythonSQLGCPGitMicrosoft AzureApache KafkaDatabricks
Requirements
- Minimum of 10 years of experience in data engineering or related disciplines, including at least 2 years in a hands-on technical lead role.
- Strong expertise in Python and SQL, with proven experience building production-grade, enterprise-scale data engineering solutions.
- Extensive experience with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure, including modern data engineering services.
- Hands-on experience with Databricks, Delta Lake, lakehouse architectures, enterprise data lakes, and cloud-native data warehouse solutions.
- Deep understanding of ETL/ELT frameworks, data modeling, orchestration, data integration patterns, and pipeline automation.
- Experience with streaming technologies such as Apache Kafka or AWS Kinesis, along with expertise in query optimization, storage optimization, and performance tuning.
- Knowledge of data governance, security, compliance, semantic modeling, and modern architectural approaches such as medallion architecture, data mesh, or data fabric.
- Experience using Git, Agile development methodologies, and collaborative software engineering best practices; familiarity with Scala or Java is an advantage.
- Strong leadership, communication, stakeholder management, and mentoring skills.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
Responsibilities
- Lead the technical design, architecture, and implementation of scalable data platforms, pipelines, and processing systems using modern cloud technologies.
- Provide hands-on technical leadership and mentor data engineering teams, promoting engineering excellence, collaboration, and continuous learning.
- Design, develop, optimize, and orchestrate robust ETL/ELT pipelines while ensuring high standards for performance, scalability, reliability, and cost efficiency.
- Establish and enforce best practices for data engineering, governance, data quality, testing, security, and operational excellence.
- Collaborate with business stakeholders and technical teams to gather requirements, lead discovery workshops, and translate business needs into scalable technical solutions.
- Drive the technical roadmap for data infrastructure, perform architecture reviews, conduct code reviews, and support technical decision-making across projects.
- Develop reusable frameworks, technical documentation, and solution accelerators while contributing to pre-sales activities, solution design, and technical proposals.
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