Architect with experience in Databricks and Sowflake
GCP Data stacks such as Bigquery knowledge preferred
Develop and implement data engineering project including enterprise data hub or Big data platform
Ability to define reference data architecture
Cloud native data platform experience in AWS or Microsoft stack
Knowledge about latest data trends including datafabric and data mesh
Robust knowledge of ETL and data transformation and data standardization approaches
Key contributor on growth of the COE and influencing client revenues through Data and analytics solutions
Lead the selection, deployment, and management of Data tools, platforms, and infrastructure.
Ability to guide technically a team of data engineers
Oversee the design, development, and deployment of Data solutions
Define, differentiate & strategize new Data services/offerings and create reference architecture assets
Drive partnerships with vendors on collaboration, capability building, go to market strategies, etc.
Guide and inspire the organization about the business potential and opportunities around Data
Network with domain experts
Collaborate with client teams to understand their business challenges and needs.
Develop and propose Data solutions tailored to client specific requirements.
Influence client revenues through innovative solutions and thought leadership.
Lead client engagements from project initiation to deployment.
Build and maintain strong relationships with key clients and stakeholders.
Build re-usable Methodologies, Pipelines & Models
Create data pipelines for more efficient and repeatable data science projects
Design and implement data architecture solutions that support business requirements and meet organizational needs
Collaborate with stakeholders to identify data requirements and develop data models and data flow diagrams
Work with cross-functional teams to ensure that data is integrated, transformed, and loaded effectively across different platforms and systems
Develop and implement data governance policies and procedures to ensure that data is managed securely and efficiently
Develop and maintain a deep understanding of data platforms, technologies, and tools, and evaluate new technologies and solutions to improve data management processes
Ensure compliance with regulatory and industry standards for data management and security.
Develop and maintain data models, data warehouses, data lakes and data marts to support data analysis and reporting.
Ensure data quality, accuracy, and consistency across all data sources.
Knowledge of ETL and data integration tools such as Informatica, Qlik Talend, and Apache NiFi.
Experience with data modeling and design tools such as ERwin, PowerDesigner, or ER/Studio
Knowledge of data governance, data quality, and data security best practices
Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
Familiarity with programming languages such as Python, Java, or Scala.
Experience with data visualization tools such as Tableau, Power BI, or QlikView.
Understanding of analytics and machine learning concepts and tools.
Knowledge of project management methodologies and tools to manage and deliver complex data projects.
Skilled in using relational database technologies such as MySQL, PostgreSQL, and Oracle, as well as NoSQL databases such as MongoDB and Cassandra. Strong expertise in cloud-based databases such as Azure datalake , Synapse, Azure data factory or AWS glue , AWS Redshift and Azure SQL.
Knowledge of big data technologies such as Hadoop, Spark, snowflake, databricks , and Kafka to process and analyze large volumes of data.
Proficient in data integration techniques to combine data from various sources into a centralized location.
Strong data modeling, data warehousing, and data integration skills.
People & Interpersonal Skills
Build and manage a high-performing team of Data engineers and other specialists.
Foster a culture of innovation and collaboration within the Data team and across the organization.
Demonstrate the ability to work in diverse, cross-functional teams in a dynamic business environment.
Candidates should be confident, energetic self-starters, with strong communication skills.
Candidates should exhibit superior presentation skills and the ability to present compelling solutions which guide and inspire.
Provide technical guidance and mentorship to the Data team
Collaborate with other stakeholders across the company to align the vision and goals
Communicate and present the Data capabilities and achievements to clients and partners
Stay updated on the latest trends and developments in the Data domain
What is required for the role?
10+ years of experience in the information technology industry with strong focus on Data engineering, architecture and preferably as data engineering lead
8+ years of data engineering or data architecture experience in successfully launching, planning, and executing advanced data projects.
Experience in working on RFP/ proposals, presales activities, business development and overlooking delivery of Data projects is highly desired
A master s or bachelor s degree in computer science, data science, information systems, operations research, statistics, applied mathematics, economics, engineering, or physics.
Candidate should have demonstrated the ability to manage data projects and diverse teams.
Should have experience in creating data and analytics solutions.
Experience in building solutions with Data solutions in any one or more domains - Industrial, Healthcare, Retail, Communication
Problem-solving, communication, and collaboration skills.
Good knowledge of data visualization and reporting tools
Ability to normalize and standardize data as per Key KPIs and Metrics