IN - Lead Cloud Data Consultant
Sourced is a global cloud consultancy that helps enterprises make the most of cloud services with a focus on security, governance and compliance. With offices around the globe, we provide professional services for securing, migrating and managing the cloud infrastructure of large enterprise customers. We specialize in configuration management, automation, cloud computing, security and data management for a wide range of industries, including financial services, media, and telecommunications companies.
Job Description
Are you a Senior Cloud Data Engineer capable of leading the design, implementation, and operational strategy of cloud-based data infrastructure for large enterprises? If yes, then we have an exciting opportunity for you! Join our team and work on challenging and impactful projects that leverage cutting-edge technologies and data-driven insights. You will have the chance to collaborate with talented and passionate professionals from diverse backgrounds and domains. You will also enjoy a supportive and hybrid work environment that fosters your growth and development.
Please note that this role will be based in Pune. Fresh graduates will not be considered.
Responsibilities:
- Lead the design, implementation, and management of scalable and efficient data architectures on cloud platforms like AWS, Azure, GCP.
- Lead the implementation of robust ETL processes to move and transform data from various sources into cloud-based data warehouses.
- Collaborate with clients to evaluate and lead the analysis of complex datasets to derive meaningful business insights.
- Lead the design and implementation of logical and physical data models to support business needs.
- Identify and implement performance tuning strategies for large-scale data processing and storage.
- Create and maintain comprehensive documentation for data processes, data models, and system architecture.
- Keep abreast of industry developments in cloud, databases, analytics, data science, AI/ML and GenAI, and how these might be applied with our customers on various use cases.
Requirements:
- More than 5 years of experience in industry (ideally banking, telecoms, and consulting) with demonstrated track record of leveraging modern data approaches on cloud platforms (AWS, Azure, GCP).
- Proficiency in SQL and experience with both relational and NoSQL databases.
- Expertise in ETL pipeline design and implementation using tools such as Azure Data Factory, Apache Airflow, AWS Kinesis Data Streams, and GCP Data Fusion and the creation of Directed Acyclic Graphs (DAGs).
- Experience with programming languages, particularly Python and Spark.
- Expertise in cloud-based data integration services like AWS Glue Data Catalog, Glue Job, Step Function, Data Lake, and Azure Data Factory.
- Experience with data quality tools like Informatica, IBM Infosphere, and Talend.
- Experience in performance monitoring and tuning for data processing and analytics systems using tools like Apache Spark UI, SQL Profiler, Grafana, Prometheus, Azure Monitor, and Apache NiFi.
- Understanding of data analysis techniques and tools like Power BI, Tableau, and Quicksight.
- Experience in data modeling and database design using tools like ERWin, Microsoft Visio, and Lucidchart.
- Knowledge of DBT (Data Build Tool) for data transformation.
- Understanding of concepts like DataMesh and DataLineage.
Are you a Senior Cloud Data Engineer capable of leading the design, implementation, and operational strategy of cloud-based data infrastructure for large enterprises? If yes, then we have an exciting opportunity for you! Join our team and work on challenging and impactful projects that leverage cutting-edge technologies and data-driven insights. You will have the chance to collaborate with talented and passionate professionals from diverse backgrounds and domains. You will also enjoy a supportive and hybrid work environment that fosters your growth and development.
Please note that this role will be based in Pune. Fresh graduates will not be considered.
Responsibilities:
- Lead the design, implementation, and management of scalable and efficient data architectures on cloud platforms like AWS, Azure, GCP.
- Lead the implementation of robust ETL processes to move and transform data from various sources into cloud-based data warehouses.
- Collaborate with clients to evaluate and lead the analysis of complex datasets to derive meaningful business insights.
- Lead the design and implementation of logical and physical data models to support business needs.
- Identify and implement performance tuning strategies for large-scale data processing and storage.
- Create and maintain comprehensive documentation for data processes, data models, and system architecture.
- Keep abreast of industry developments in cloud, databases, analytics, data science, AI/ML and GenAI, and how these might be applied with our customers on various use cases.
Requirements:
- More than 5 years of experience in industry (ideally banking, telecoms, and consulting) with demonstrated track record of leveraging modern data approaches on cloud platforms (AWS, Azure, GCP).
- Proficiency in SQL and experience with both relational and NoSQL databases.
- Expertise in ETL pipeline design and implementation using tools such as Azure Data Factory, Apache Airflow, AWS Kinesis Data Streams, and GCP Data Fusion and the creation of Directed Acyclic Graphs (DAGs).
- Experience with programming languages, particularly Python and Spark.
- Expertise in cloud-based data integration services like AWS Glue Data Catalog, Glue Job, Step Function, Data Lake, and Azure Data Factory.
- Experience with data quality tools like Informatica, IBM Infosphere, and Talend.
- Experience in performance monitoring and tuning for data processing and analytics systems using tools like Apache Spark UI, SQL Profiler, Grafana, Prometheus, Azure Monitor, and Apache NiFi.
- Understanding of data analysis techniques and tools like Power BI, Tableau, and Quicksight.
- Experience in data modeling and database design using tools like ERWin, Microsoft Visio, and Lucidchart.
- Knowledge of DBT (Data Build Tool) for data transformation.
- Understanding of concepts like DataMesh and DataLineage.
