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Databricks SME Professional
8-9 years
Kolkata, Mumbai, New Delhi + 4 more
1 vacancy
Databricks SME Professional
Zensar Technologies
posted 5d ago
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Flexible timing
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Job Description
Databricks Expert will be required to set up the Databricks Platform on AWS, so he or she needs to be proficient with infrastructure as code technology such as CloudFormation and Terraform to work together with the Platform Engineering team.
Must have knowledge in Networking and Security Architecture for a successful implementation.
- Design & Build Data Pipelines : Develop, optimize, and manage large-scale data engineering workflows using Databricks and Apache Spark , ensuring scalable and efficient data processing.
- Data Lake & Delta Lake : Build and manage lake houses/data lakes using Databricks Delta Lake to ensure high-performance, scalable, and reliable storage for structured and unstructured data.
- with Cross-Functional Teams : Work with data scientists, analysts, and business stakeholders to understand data needs, provide insights, and deliver solutions using Databricks.
- Performance Tuning & Optimization : Tune and optimize Spark-based jobs and other Databricks workflows for high performance and low latency across large datasets.
- Data Integration : Integrate and orchestrate data from multiple sources (e.g., databases, APIs, cloud services) into the Databricks environment, ensuring data quality and consistency.
- Cloud Infrastructure Management : Leverage cloud platforms (e.g., AWS, Azure, GCP) for efficient use of Databricks clusters, ensuring cost optimization and scalability.
- Machine Learning Pipeline Development : Collaborate with data scientists to design and implement end-to-end machine learning pipelines, utilizing MLflow for model tracking, versioning, and deployment.
- Model Deployment & Monitoring : Collaborate on model deployment strategies within Databricks , using MLflow for tracking, managing experiments, and deploying models into production environments.
- Automation & CI/CD : Implement continuous integration and continuous delivery (CI/CD) pipelines to automate the deployment of data pipelines and machine learning models.
Skills & Qualifications:
Required:
- Bachelor s / Master s degree in computer science , Engineering or a related field.
- 7+ years of experience in data engineering , with hands-on expertise in Databricks and Apache Spark .
- Proficiency in Python and SQL , with extensive experience in data processing and model development in Databricks .
- Strong experience with Databricks Delta Lake for efficient data storage and management.
- Experience building and optimizing ETL / ELT pipelines for large-scale data processing and integration.
- Knowledge of cloud platforms (AWS, Azure, or GCP) and experience managing Databricks environments in the cloud.
- Experience in creating scalable data models, workflows, and pipelines for structured and unstructured data.
- Expertise in performance tuning and optimization of Spark-based jobs in Databricks .
- Having worked under Agile project environment
Preferred:
- Databricks certifications such as Apache Spark Programming, Data Engineer Associate or Professional.
- Experience with Apache Kafka or other streaming technologies in Databricks for real-time data processing.
- Knowledge of DevOps practices and CI/CD for automating data workflows and model deployments.
- Experience with data governance , security , and privacy best practices in cloud environments.
Soft Skills:
- Strong problem-solving abilities and the ability to think critically about data challenges.
- Excellent communication skills, with the ability to explain complex data engineering concepts to non-technical stakeholders.
- Adaptability and willingness to stay up to date with the latest Databricks and data engineering trends and tools.
Employment Type: Full Time, Permanent
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Flexible timing
Monday to Friday
No travel
Day Shift
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