Design and implement a centralized data fabric ensuring governance, trust, and cost efficiency. optimize data ingestion pipelines and etl workflows for batch and real-time processing. develop and maintain an enterprise data catalog enriched with metadata to enhance discoverability. implement data governance frameworks using unity catalog and define policies for centralized and self-governed domains. enable self-service analytics with scalable databricks and thoughtspot solutions. manage and integrate internal and external data sources, ensuring quality and eliminating redundancies. collaborate with engineering, qa, and business teams to align data strategies with business goals. support ml/ai, analytics, and martech initiatives by providing a robust data infrastructure. what we're looking for:extensive experience with databricks (azure) and its ecosystem. strong expertise in data governance, metadata management, and enterprise data catalogs. proficiency in sql, spark, and python for data processing and transformation. experience with azure data factory or similar orchestration tools (e.g., airflow). knowledge of bi and self-service analytics tools like thoughtspot or tableau. hands-on experience with cloud data platforms (azure, gcp preferred). solid understanding of batch and real-time data processing architectures. ability to assess and optimize data infrastructure costs. strong problem-solving skills and ability to translate business needs into scalable solutions. excellent communication and collaboration skills in cross-functional environments. #j-1880...
Job responsibilities 1. stay up-to-date with the latest advancements in machine learning by exploring and drawing insights from state-of-the-art research papers. leverage this knowledge to design and develop innovative machine learning models tailored to our specific needs. 2. translate conceptual models into practical implementations, utilizing programming languages and machine learning frameworks. train and fine-tune models to achieve optimal performance and accuracy. 3. drive the deployment process of machine learning models into production environments. collaborate with cross-functional teams to ensure smooth integration and scalability of the models. 4. apply the best mlops (machine learning operations) practices and principles throughout the entire modeling workflow. streamline processes for efficient development, testing, and deployment of machine learning solutions. 5. dive deep into problem domains to gain a comprehensive understanding of challenges and opportunities. analyze and preprocess data to extract valuable insights for model improvement. 6. propose and experiment with novel ideas and approaches to tackle complex problems. explore creative ways to leverage data and develop new concepts that could potentially revolutionize the field. 7. collaborate with a team of skilled professionals, including data scientists, engineers, and domain experts. foster a collaborative environment that encourages knowledge sharing and continuous learning. minimum requirements 1. bachelor degree in computer science, software or electrical engineering, or comparable pr...
Design and implement a centralized data fabric ensuring governance, trust, and cost efficiency. optimize data ingestion pipelines and etl workflows for batch and real-time processing. develop and maintain an enterprise data catalog enriched with metadata to enhance discoverability. implement data governance frameworks using unity catalog and define policies for centralized and self-governed domains. enable self-service analytics with scalable databricks and thoughtspot solutions. manage and integrate internal and external data sources , ensuring quality and eliminating redundancies. collaborate with engineering, qa, and business teams to align data strategies with business goals. support ml/ai, analytics, and martech initiatives by providing a robust data infrastructure. what we’re looking for: extensive experience with databricks (azure) and its ecosystem. strong expertise in data governance, metadata management, and enterprise data catalogs . proficiency in sql, spark, and python for data processing and transformation. experience with azure data factory or similar orchestration tools (e.g., airflow). knowledge of bi and self-service analytics tools like thoughtspot or tableau. hands-on experience with cloud data platforms (azure, gcp preferred). solid understanding of batch and real-time data processing architectures . ability to assess and optimize data infrastructure costs . strong problem-solving skills and ability to translate business needs into scalable solutions. excellent communication and collaboration skills in cross-functiona...
Design and implement a centralized data fabric ensuring governance, trust, and cost efficiency. optimize data ingestion pipelines and etl workflows for batch and real-time processing. develop and maintain an enterprise data catalog enriched with metadata to enhance discoverability. implement data governance frameworks using unity catalog and define policies for centralized and self-governed domains. enable self-service analytics with scalable databricks and thoughtspot solutions. manage and integrate internal and external data sources, ensuring quality and eliminating redundancies. collaborate with engineering, qa, and business teams to align data strategies with business goals. support ml/ai, analytics, and martech initiatives by providing a robust data infrastructure. what we’re looking for: extensive experience with databricks (azure) and its ecosystem. strong expertise in data governance, metadata management, and enterprise data catalogs. proficiency in sql, spark, and python for data processing and transformation. experience with azure data factory or similar orchestration tools (e.g., airflow). knowledge of bi and self-service analytics tools like thoughtspot or tableau. hands-on experience with cloud data platforms (azure, gcp preferred). solid understanding of batch and real-time data processing architectures. ability to assess and optimize data infrastructure costs. strong problem-solving skills and ability to translate business needs into scalable solutions. excellent communication and collaboration skills in cross-functional environments. #j-18...
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