State Street
Financial Services
LeadCloudDataEngineer(Databricks)-AssistantVicePresident
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“Lead Cloud Data Engineer (Databricks) - Assistant Vice President at State Street. Skills: Databricks, Spark, Data pipelines, Cloud data engineering. Design scalable data pipelines. Develop scalable data pipelines”
What You'll Achieve.
Deliver high-quality data solutions; Deliver reliable data solutions
Industry & Context.
Problem-solving mindset; Data-driven decisions
What They're Looking For.
Must Have
14-18 years hands-on experience, Databricks and Apache Spark experience, Data Engineering and Big Data technologies experience, Cloud platforms experience (AWS or Azure), SQL and Python/Scala programming skills, Data pipeline design experience, ETL/ELT frameworks experience, Data modeling experience, Performance optimization experience, Scalability of data solutions experience
Nice to Have
Streaming technologies experience (Kafka), Delta Lake knowledge, Data lakehouse architecture knowledge, CI/CD and DevOps practices experience, Containerization tools familiarity (Docker, Kubernetes), Data governance exposure, Regulatory environments exposure
What You'll Do.
Design scalable data pipelines
Develop scalable data pipelines
Maintain scalable data pipelines
Design data workflows
Develop data workflows
Maintain data workflows
Optimize ETL pipelines
Optimize ELT pipelines
Process near real-time data
Collaborate with architects
Collaborate with business stakeholders
Translate requirements to implementation
Ensure data governance
Ensure data consistency
Perform performance tuning
Optimize cost efficiency
Support production deployments
Ensure reliability of data systems
How You'll Work.
Team & Collaboration
Agile teams; Global distributed teams; Across business stakeholders; Across architecture stakeholders; Across engineering stakeholders
Communication Scope
Communicate technical concepts
Process & Methodology
Agile
Full Job Description
**Who we are looking for:** * A strong Sr. Data Engineer with deep hands-on expertise in Databricks and modern data engineering platforms. * Proven ability to design, build, and optimize scalable data pipelines on cloud platforms. * Experience working in agile teams and collaborating across business, architecture, and engineering stakeholders. * Strong problem-solving mindset with focus on delivering high-quality, reliable data solutions. **What you will be responsible for:** * Design, develop, and maintain scalable data pipelines and workflows using Databricks and Spark. * Build and optimize ETL/ELT pipelines for batch and near real-time data processing. * Collaborate with architects and business stakeholders to translate requirements into technical implementation. * Ensure data quality, governance, and consistency across data platforms. * Perform performance tuning and optimize cost efficiency of data workloads. * Support production deployments, troubleshoot issues, and ensure reliability of data systems. **What we value:** * Strong engineering and ownership mindset with attention to quality and performance. * Collaboration and ability to work effectively in global distributed teams. * Continuous learning and adoption of modern data engineering practices. * Ability to communicate technical concepts clearly to both technical and non-technical stakeholders. **Mandatory skills / experience:** * 14-18 Hands-on experience with Databricks and Apache Spark (Python/Scala). * Strong experience in Data Engineering and Big Data technologies. * Experience with cloud platforms such as AWS or Azure. * Strong SQL and Python/Scala programming skills. * Experience with data pipeline design, ETL/ELT frameworks, and data modeling. * Experience in performance optimization and scalability of data solutions. **Additional requirements / Good to have skills:** * Experience with streaming technologies such as Kafka. * Knowledge of Delta Lake and data lakehouse architecture. * Experience w
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