Senior Data Architect

13 hours ago

Bangalore Division, India Saaki Argus & Averil Consulting Full time

About the company: An IT Service Management Company. Key Responsibilities: Create and put into action solid data architectures that facilitate business needs and promote data-driven decision-making. Using Snowflake, Databricks, Hadoop, and open-source data lake architectures, create and manage scalable data models, data warehouses, and data lakes. Oversee data engineering initiatives to construct and enhance ETL pipelines while guaranteeing data integrity and quality. Work together with cross-functional teams to comprehend data requirements and convert them into technological fixes. Put best practices for compliance, security, and data governance into action. To guarantee precise and reliable data flow, do data mapping, data profiling, and data lineage analysis. Keep abreast of emerging technologies and trends in the industry to continuously enhance our data architecture; Offer technical leadership and guidance to junior data engineers and architects. Qualifications: A bachelor's or master's degree in computer science, information technology, or a similar discipline is required. 14 15 years of expertise in data engineering, data modeling, and data architecture. Demonstrated proficiency in open-source data lake architectures, Snowflake, Databricks, or Hadoop, along with practical knowledge of their corresponding tools and frameworks. Excellent knowledge in Python, SQL, and other pertinent programming languages. Knowledge with cloud computing platforms including Google Cloud, AWS, and Azure. A thorough understanding of data warehousing, data lake topologies, and ETL procedures. Outstanding problem-solving abilities and the capacity to operate in a fast-paced, team-oriented setting. Excellent interpersonal and communication skills, including the capacity to explain intricate technical ideas to stakeholders who are not technical. Preferred Skills: Knowledge of data visualization software such as Tableau or Power BI. An understanding of AI and machine learning principles. Knowledge of data governance tools and frameworks. Experience in pre-sales, including the capacity to interact with customers and assist sales teams in developing data solutions. Proposal drafting, solution design, proposal defense, and estimation experience.

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