- अनुभव
- कोणतेही
- पगार
- —
- रिक्त जागा
- 1
- पोस्ट केले
- २ तासांपूर्वी
- कार्य मोड
- कार्यालयात
- सारांश
- अर्ज करणे आवश्यक आहे
तुम्ही जिथे काम कराल
नोकरीचे वर्णन
About the Role
This position entails leading and overseeing large-scale Data Engineering and Data Modernization programs. The role demands hands-on management of data-centric projects from start to finish including effort estimation, defining scope, formulating project plans, setting timelines, allocating teams, and maintaining stakeholder communication.
Key Responsibilities
- Lead the delivery of Data Lake creation and migration projects.
- Manage PySpark migration and optimization initiatives focusing on performance and scalability.
- Translate business requirements into effective data solutions, actively addressing risks, challenges, and interdependencies.
- Architect and execute modern data frameworks including Data Lakes, Data Warehouses, and Lakehouse implementations.
- Collaborate with business leaders, architects, and engineering teams to establish data strategies and development roadmaps.
- Provide technical guidance and mentorship to data engineering teams.
- Enforce best practices related to data governance, quality, security, compliance, and performance tuning.
- Drive modernization efforts for data platforms across various cloud setups.
- Review technical designs, architectural proposals, and deployment methods.
- Manage project scope, resource distribution, risk mitigation, and delivery schedules.
- Champion Agile methodologies ensuring effective project execution.
Required Qualifications and Skills
- Proven track record in managing data projects end-to-end including planning, resourcing, and stakeholder engagement.
- Proficient with modern data technologies such as PySpark, SQL, CML, and Python on cloud infrastructures, preferably Google Cloud Platform.
- Experienced in executing Data Lake implementations, migrations, PySpark migration projects, and major data transformation initiatives.
- Technical proficiency in Python, Spark SQL, ETL/ELT frameworks, and Hadoop ecosystem.
- Sound knowledge of data lakes and lakehouse architectural models and distributed data processing.
- Understanding of data modeling, integration patterns, both batch and real-time data processing.
- Familiarity with cloud services like AWS, Azure, and GCP.
- Hands-on experience with data migration tactics, performance optimization, and CI/CD as well as DevOps practices applicable to data platforms.
Preferred Skills
- Experience with Databricks, Delta Lake, Apache Airflow, Kafka, Snowflake, Kubernetes, and Docker.
- Background in banking, financial services, or large-scale enterprise environments.
- Familiarity with frameworks for data governance and data quality.