Kinesis Jobs in Pune

Job Title: Senior AWS Data Engineer Experience: 5+ years Location: Kharadi, Pune Role & Responsibilities Design, develop, and optimize scalable data pipelines and ETL workflows using AWS services such as AWS Glue, Lambda, and Step Functions. Implement and maintain data lakes and data warehouses on AWS platforms including S3, Redshift, and Athena. Develop and manage both real-time and batch data processing solutions. Ensure data security, governance, and compliance following industry best practices. Collaborate with data scientists, analysts, and business stakeholders to deliver actionable, data-driven solutions. Optimize query performance and troubleshoot data issues proactively. Automate infrastructure deployment using Infrastructure as Code (IaC) tools like Terraform or CloudFormation. Implement monitoring, logging, and alerting frameworks using AWS CloudWatch, Prometheus, or equivalent tools. Mentor junior engineers and actively contribute to data engineering best practices and standards. Required Skills & Qualifications 5+ years of experience in data engineering, with at least 3 years focused on AWS cloud services. Strong hands-on experience with AWS services including Glue, Redshift, S3, Lambda, EMR, and Athena. Proficient in SQL, Python, and Spark for data processing and analytics. Experience designing and implementing ETL/ELT pipelines. Familiarity with DevOps practices, CI/CD pipelines, and automation tools such as Terraform, CloudFormation, and Jenkins. Deep understanding of data governance, security protocols, and compliance frameworks. Experience with real-time data streaming and processing technologies such as Kafka, Kinesis, or similar tools. Knowledge of database optimization techniques including indexing and partitioning.

Job Title: Senior Staff Software Engineer (Foundation) Company: Druva Location: Pune, India About Druva: Druva empowers organizations with cyber, data, and operational resilience through the Data Resiliency Cloud the industry s first and only SaaS solution at scale. Our platform simplifies data protection, streamlines governance, and provides unparalleled data visibility and insights, enabling customers to accelerate cloud adoption. Trusted by thousands of enterprises, including 60 of the Fortune 500, Druva eliminates complex infrastructure and management costs by delivering data resilience through a single platform spanning multiple geographies and cloud environments. About the Role: The Foundation team at Druva designs and develops a highly scalable, petabyte-scale distributed cloud file system built on AWS. This service-oriented system handles critical features such as file system metadata management, versioning, and eventual consistency using AWS services like S3, DynamoDB, and Kinesis. Beyond the core file storage engine which supports backup storage for all Druva products the team builds and maintains allied components like indexing engines, key-value stores, and big data pipelines to enable scalable search, analytics, and compliance capabilities. As a Senior Staff Software Engineer, you will collaborate closely with cross-functional teams, architects, and DevOps to define high-level and low-level designs (HLD/LLD) for advanced data security and management services. You will stay abreast of emerging trends in data security, platforms, technologies, and APIs, applying these insights to enhance existing features and develop new capabilities. You will also mentor and guide junior engineers, fostering a culture of high-quality, high-velocity software development. Key Skills & Experience: 5 to 7 years of experience building enterprise-grade software products. Expertise in designing and implementing SaaS solutions at scale. Proficiency in Python or Golang for software development. Deep knowledge and hands-on experience with cloud storage and data management systems. Proven experience building storage systems focused on securing and protecting data at scale, including managing data and metadata. Prior experience working on data protection products is highly desirable. Familiarity with cloud platforms such as AWS and Azure is a plus. Strong hands-on developer with excellent communication and collaboration skills. Ability to influence architecture, design, and implementation for timely delivery of business outcomes. Desirable: Strong written and verbal communication skills. Experience with Agile methodologies (Scrum). In-depth knowledge of AWS cloud technologies. Responsibilities: Collaborate with architects, developers, and DevOps to define HLD and LLD for data security and management services and features. Monitor and evaluate emerging trends in data security, management platforms, technologies, and APIs to refine and develop features. Lead the integration of data management tools and applications to enhance product quality and user experience. Promote best practices and principles of high-quality SaaS software development. Mentor and train junior engineers on data management, security principles, and agile development methodologies. Qualifications: Bachelor s or Master s degree in Computer Science, Engineering, or a related field (Advanced degree preferred). Qualification : Bachelors or Masters degree in Computer Science, Engineering, or a related field (Advanced degree preferred).

Job Title: Staff Data / Machine Learning Engineer Company: Druva Location: Pune, Maharashtra, India About Druva: Druva, the autonomous data security company, delivers data protection on autopilot through a 100% SaaS, fully managed platform that secures and recovers data from all threats. The Druva Data Security Cloud guarantees data availability, confidentiality, and integrity providing customers with autonomous protection, rapid incident response, and guaranteed data recovery. Trusted by over 6,000 customers worldwide including 65 of the Fortune 500 Druva safeguards business-critical data in today s connected world. Backed by over $350M in venture capital, Druva protects more than 200 PB of data globally and offers a $10 million Data Resiliency Guarantee against cyber threats. The Role & Team: Join Druva s Business Intelligence team, where data drives key insights and fuels operational and strategic decisions. As a Staff Data/Analytics/ML Engineer, you will lead the development of data-to-insights recommendation engines and drive collaboration across teams to deliver impactful, data-driven solutions. This is a high-impact role working alongside expert engineers and product leaders, leveraging industry-leading data platforms and tools. What You ll Do: Bridge the gap between data engineering, analytics, and machine learning to unlock actionable business insights. Collaborate cross-functionally with Product, Engineering, GTM, and Customer Success teams to build data-driven solutions that enhance decision-making and business outcomes. Design, build, and maintain scalable data pipelines and infrastructure supporting analytics, machine learning, and operational workflows. Develop and optimize data models for efficient analytics and reporting across large datasets. Lead feature engineering, model training, and deployment pipelines for real-time and batch ML/AI applications. Drive architectural improvements in data governance, observability, and platform scalability. Evaluate and implement cutting-edge data tools and platforms including Reverse ETL, MLOps, and DataOps frameworks. Mentor and guide data engineers, analysts, and ML practitioners, fostering technical excellence and collaboration. Translate complex business requirements into technical deliverables, prioritizing initiatives that maximize impact. What We Are Looking For: Bachelor s or Master s degree in Computer Science, Data Science, Engineering, Statistics, or a related field. 7+ years experience spanning data engineering, analytics engineering, and machine learning with a strong technical foundation in all three areas. Expertise in modern data stacks: Snowflake, dbt, Airflow, Spark, and cloud platforms (AWS, GCP, Azure). Proficiency with BI and analytics tools such as Looker, Sigma, Tableau, Power BI, or equivalents. Strong skills in SQL, Python, and distributed data processing frameworks (Spark, Dask, etc.). Experience designing and maintaining data pipelines, ETL/ELT workflows, and data transformations for analytics and ML use cases. Familiarity with ML frameworks like TensorFlow, PyTorch, Scikit-learn, and MLOps lifecycle management. Deep knowledge of data modeling, architecture, and governance best practices. Proven problem-solver who thrives in ambiguity and designs robust data solutions. Experience working in Agile environments with strong prioritization and collaboration skills. Excellent communication skills, capable of simplifying complex technical topics for non-technical stakeholders. Bonus Points For: Experience with Generative AI, LLMs, and integrating AI into business workflows. Knowledge of streaming architectures (Kafka, Kinesis, Pub/Sub) and real-time analytics. Familiarity with Data Contracts, Data Quality frameworks, or Data Mesh architectures. Experience with Reverse ETL tools such as Salesforce, Census, Hightouch, or Segment for operational analytics. If you re passionate about driving data innovation at scale and want to work in a dynamic environment protecting the world s critical data, Druva invites you to join our team! Qualification : Bachelors or Masters degree in Computer Science, Data Science, Engineering, Statistics, or a related field.