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Job Description Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner. We are one of the highest-rated employers on Glassdoor. If you are passionate about working on unstructured business problems that can be solved using data, we would like to talk to you. Responsibilities Mentorship and solution support to client-facing Data Engineers across key accounts Review data engineer work and promote best practices and frameworks to improve productivity and client satisfaction Collaborate with DevOps and MLE teams to onboard and productionize Data Science models at scale Implement and manage production processes for data ingestion, transformation, storage, reporting, and integration Coordinate between onsite and offshore leadership for updates Engagement with Clients Review and advise on architecture requirements Recommend strategies for resiliency, security, and cost optimization Design and develop analytics frameworks, data lakes, and cloud-based data solutions Create scalable data ingestion frameworks with data quality and metadata management Requirements Bachelors degree in Computer Science or related field 10+ years in IT with experience in system administration and automation 3-5 years of hands-on experience with AWS or other cloud platforms in data and analytics 1+ years deploying services on Kubernetes 3-5 years of expertise in cloud data platforms, big data, and DevOps, with proficiency in Python, Java, or Scala 1-2 years experience with cloud data warehouses (Redshift, Snowflake, BigQuery) Knowledge of building Data Lakes, Data Pipelines, and Data Storage on cloud Experience with big data frameworks like Spark or Flink Knowledge of delta lake or similar technologies Exposure to operationalizing ML models at scale on cloud Understanding of DevSecOps and cloud security Experience working with Scrum Agile methodologies Proficiency in SQL, NoSQL, and Object Stores Experience working in onsite/offshore models Knowledge of networking, firewalls, load balancers, etc. AWS Professional Architect Certification preferred Excellent communication skills for technical and executive interactions Benefits Opportunities for career growth in a fast-paced, entrepreneurial environment with significant responsibilities. #J-18808-Ljbffr