Senior Data Architect
Job Description
About the company:
\nAn IT Service Management Company.
\nKey Responsibilities:
\nCreate and put into action solid data architectures that facilitate business needs and promote data-driven decision-making.
\nUsing Snowflake, Databricks, Hadoop, and open-source data lake architectures, create and manage scalable data models, data warehouses, and data lakes.
\nOversee data engineering initiatives to construct and enhance ETL pipelines while guaranteeing data integrity and quality.
\nWork together with cross-functional teams to comprehend data requirements and convert them into technological fixes.
\nPut best practices for compliance, security, and data governance into action.
\nTo guarantee precise and reliable data flow, do data mapping, data profiling, and data lineage analysis.
\nKeep 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.
\nQualifications:
\nA bachelor's or master's degree in computer science, information technology, or a similar discipline is required.
\n14 15 years of expertise in data engineering, data modeling, and data architecture.
\nDemonstrated proficiency in open-source data lake architectures, Snowflake, Databricks, or Hadoop, along with practical knowledge of their corresponding tools and frameworks.
\nExcellent knowledge in Python, SQL, and other pertinent programming languages.
\nKnowledge with cloud computing platforms including Google Cloud, AWS, and Azure.
\nA thorough understanding of data warehousing, data lake topologies, and ETL procedures.
\nOutstanding problem-solving abilities and the capacity to operate in a fast-paced, team-oriented setting.
\nExcellent interpersonal and communication skills, including the capacity to explain intricate technical ideas to stakeholders who are not technical.
\nPreferred Skills:
\nKnowledge of data visualization software such as Tableau or Power BI.
\nAn understanding of AI and machine learning principles.
\nKnowledge of data governance tools and frameworks.
\nExperience in pre-sales, including the capacity to interact with customers and assist sales teams in developing data solutions.
\nProposal drafting, solution design, proposal defense, and estimation experience.
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