745 Amazon Redshift Jobs - Page 8

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities,collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client"s challenges of today and tomorrow.Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose. Your role In this role you will play a key role in Data Strategy - We are looking for a 8+ years experience in Data Strategy (Tech Architects, Senior BAs) who will support our product, sales, leadership teams by creating data-strategy roadmaps. The ideal candidate is adept at understanding the as-is enterprise data models to help Data-Scientists/ Data Analysts to provide actionable insights to the leadership. They must have strong experience in understanding data, using a variety of data tools. They must have a proven ability to understand current data pipeline and ensure minimal cost-based solution architecture is created & must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Identify, design, and recommend internal process improvementsautomating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. & identify data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to create frameworks for digital twins/ digital threads having relevant experience in data exploration & profiling, involve in data literacy activities for all stakeholders & coordinating with cross functional team ; aka SPOC for global master data Your Profile 8+ years of experience in a Data Strategy role, who has attained a Graduate degree in Computer Science, Informatics, Information Systems, or another quantitative field. They should also have experience using the following software/tools - Experience with understanding big data toolsHadoop, Spark, Kafka, etc. & experience with understanding relational SQL and NoSQL databases, including Postgres and Cassandra/Mongo dB & experience with understanding data pipeline and workflow management toolsLuigi, Airflow, etc. 5+ years of Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.Postgres/ SQL/ Mongo & 2+ years working knowledge in Data StrategyData Governance/ MDM etc. Having 5+ years of experience in creating data strategy frameworks/ roadmaps, in Analytics and data maturity evaluation based on current AS-is vs to-be framework and in creating functional requirements document, Enterprise to-be data architecture. Relevant experience in identifying and prioritizing use case by for business; important KPI identification opex/capex for CXO"s with 2+ years working knowledge in Data StrategyData Governance/ MDM etc. & 4+ year experience in Data Analytics operating model with vision on prescriptive, descriptive, predictive, cognitive analytics What you will love about working here We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. Location - Bengaluru,Mumbai,Chennai,Noida,Pune,Hyderabad

We are looking for an experienced Data Modelling professional, proficient in tools such as Erwin and ER/Studio. A strong understanding of Azure Databricks, Snowflake/Redshift, SAP HANA, and advanced SQL is required. Prior experience in leading teams is also preferred.

Job Title : Data Engineer (DE) / SDE Data Location Bangalore Experience range 3-15 What we offer Our mission is simple Building trust. Our customer's trust in us is not merely about the safety of their assets but also about how dependable our digital offerings are. Thats why, we at Kotak Group are dedicated to transforming banking by imbibing a technology-first approach in everything we do, with an aim to enhance customer experience by providing superior banking services. We welcome and invite the best technological minds in the country to come join us in our mission to make banking seamless and swift. Here, we promise you meaningful work that positively impacts the lives of many. About our team DEX is a central data org for Kotak Bank which manages entire data experience of Kotak Bank. DEX stands for Kotaks Data Exchange. This org comprises of Data Platform, Data Engineering and Data Governance charter. The org sits closely with Analytics org. DEX is primarily working on greenfield project to revamp entire data platform which is on premise solutions to scalable AWS cloud-based platform. The team is being built ground up which provides great opportunities to technology fellows to build things from scratch and build one of the best-in-class data lake house solutions. The primary skills this team should encompass are Software development skills preferably Python for platform building on AWS; Data engineering Spark (pyspark, sparksql, scala) for ETL development, Advanced SQL and Data modelling for Analytics. The org size is expected to be around 100+ member team primarily based out of Bangalore comprising of ~10 sub teams independently driving their charter. As a member of this team, you get opportunity to learn fintech space which is most sought-after domain in current world, be a early member in digital transformation journey of Kotak, learn and leverage technology to build complex data data platform solutions including, real time, micro batch, batch and analytics solutions in a programmatic way and also be futuristic to build systems which can be operated by machines using AI technologies. The data platform org is divided into 3 key verticals Data Platform This Vertical is responsible for building data platform which includes optimized storage for entire bank and building centralized data lake, managed compute and orchestrations framework including concepts of serverless data solutions, managing central data warehouse for extremely high concurrency use cases, building connectors for different sources, building customer feature repository, build cost optimization solutions like EMR optimizers, perform automations and build observability capabilities for Kotaks data platform. The team will also be center for Data Engineering excellence driving trainings and knowledge sharing sessions with large data consumer base within Kotak. Data Engineering This team will own data pipelines for thousands of datasets, be skilled to source data from 100+ source systems and enable data consumptions for 30+ data analytics products. The team will learn and built data models in a config based and programmatic and think big to build one of the most leveraged data model for financial orgs. This team will also enable centralized reporting for Kotak Bank which cuts across multiple products and dimensions. Additionally, the data build by this team will be consumed by 20K + branch consumers, RMs, Branch Managers and all analytics usecases. Data Governance The team will be central data governance team for Kotak bank managing Metadata platforms, Data Privacy, Data Security, Data Stewardship and Data Quality platform. If youve right data skills and are ready for building data lake solutions from scratch for high concurrency systems involving multiple systems then this is the team for you. You day to day role will include Drive business decisions with technical input and lead the team. Design, implement, and support an data infrastructure from scratch. Manage AWS resources, including EC2, EMR, S3, Glue, Redshift, and MWAA. Extract, transform, and load data from various sources using SQL and AWS big data technologies. Explore and learn the latest AWS technologies to enhance capabilities and efficiency. Collaborate with data scientists and BI engineers to adopt best practices in reporting and analysis. Improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers. Build data platforms, data pipelines, or data management and governance tools. BASIC QUALIFICATIONS for Data Engineer/ SDE in Data Bachelor's degree in Computer Science, Engineering, or a related field 3-5 years of experience in data engineering Strong understanding of AWS technologies, including S3, Redshift, Glue, and EMR Experience with data pipeline tools such as Airflow and Spark Experience with data modeling and data quality best practices Excellent problem-solving and analytical skills Strong communication and teamwork skills Experience in at least one modern scripting or programming language, such as Python, Java, or Scala Strong advanced SQL skills PREFERRED QUALIFICATIONS AWS cloud technologiesRedshift, S3, Glue, EMR, Kinesis, Firehose, Lambda, IAM, Airflow Prior experience in Indian Banking segment and/or Fintech is desired. Experience with Non-relational databases and data stores Building and operating highly available, distributed data processing systems for large datasets Professional software engineering and best practices for the full software development life cycle Designing, developing, and implementing different types of data warehousing layers Leading the design, implementation, and successful delivery of large-scale, critical, or complex data solutions Building scalable data infrastructure and understanding distributed systems concepts SQL, ETL, and data modelling Ensuring the accuracy and availability of data to customers Proficient in at least one scripting or programming language for handling large volume data processing Strong presentation and communications skills. For Managers, Customer centricity, obsession for customer Ability to manage stakeholders (product owners, business stakeholders, cross function teams) to coach agile ways of working. Ability to structure, organize teams, and streamline communication. Prior work experience to execute large scale Data Engineering projects

Overview The Tech Strategy & Enterprise Solutions Consumer Capability at PepsiCo drives personalization at scale by leveraging best-in-class technology stack. The team elevates consumer engagement through Salesforce Marketing Cloud, Data Cloud, MCP, and Service Cloud, enabling targeted campaigns and loyalty initiatives. Responsibilities Collaborate with cross-functional teams, including Business Analysts, Product Owners, and IT teams, to deeply understand Salesforce functionalities, assess risks, and develop robust solutions aligned with business requirements. Govern and maintain compliance with standards, including ISO and CMMI, to ensure alignment with organizational goals. Document solutions with a meticulous and detail-oriented approach, clearly articulating the how and why to build a comprehensive and accessible knowledge base. Act as the SPOC for Salesforce-related queries, ensuring timely and effective resolution. Manage user accounts, security settings, and data tasks such as imports, exports, and cleansing. Customize and maintain Salesforce objects, workflows, dashboards, and reports while ensuring usability and scalability. Monitor system performance, troubleshoot issues, and integrate Salesforce with third-party tools. Qualifications Mandatory Technical Skills Expertise in Salesforce administration, including custom objects, sharing settings, profiles, role hierarchies, Salesforce Shield, and GDPR compliance for secure system management. Proficiency in understanding the Salesforce Data Cloud elated metadata and working Proficiency in Salesforce reporting, analytics, and data visualization tools for decision-making. Familiarity with risk assessment frameworks for system development. Salesforce DataCloud Consultant (required) Salesforce Administrator Certification (required); Advanced certifications like Salesforce Advanced Administrator and Platform App Builder are preferred. Mandatory Non-Technical Skills A keen eye for detail and a proactive approach to identifying issues and inefficiencies. Strong problem-solving skills with the ability to develop and implement long-term solutions. A governance-focused mindset with a commitment to maintaining high operational standards. Effective communication and interpersonal skills to act as a trusted SPOC for stakeholders.

Overview This role will play a pivotal role within the Control & Governance team of the procurement team and has a main objective to contribute to risk mitigation, policy implementation, and the overall effectiveness of our procurement governance framework for AMESA Sector (Ind and Pak) and APAC sector (ANZ market). Purpose Work with key stakeholders to maximize the main benefits that myBUY has for the company in terms of Compliance & Policy Adherence Guarantee all in-scope purchases are aligned to the corporate policy and procedures. Risk Assessment and Mitigationidentify potential risks and implement risk mitigation strategies. Process StandardizationClosely work with myBUY control, compliance and governance GPO to drive standardization across all sectors. Scope The function holder is covering for AMESA Sector (Ind and Pak) and APAC sector (ANZ market). Responsibilities Compliance & Policy Adherence Monitor procurement activities to ensure strict compliance with internal policies, procedures, and relevant regulatory requirements. Conduct regular reviews of purchase orders to identify any deviations/non-compliant activities from the policy. Continuously monitor changes in relevant global policies and regulations and perform impact analysis on the existing controls and implement the required changes to the controls upon alignment from controls team. Ensure the myBUY Policies and guidelines are in line with P2P and Global Procurement policy and guidelines. Collaborate with key stakeholders from control and procurement teams to develop, update, and communicate procurement controls matrix. Prepare training materials to employees within the department to enhance awareness of compliance obligations. Ensure that the GCS scope controls are executed as per the controls design matrix and ensure the same has been documented in the GCS portal on timely manner. Act as a liaison between the procurement department, Internal & External auditor management. Collaborate during audits, providing necessary documentation, explanations, and implementing corrective actions in a timely manner. Risk Assessment and Mitigation Develop and implement risk mitigation strategies, working closely with procurement stakeholders and continuously monitor the effectiveness of these strategies and make adjustments as needed. (e.g.Governance calls) Support and review myBUY CR initiatives/system upgrade with subject matter experts (SMEs) in AMESA and APAC. Process Standardization Closely work with myBUY myBUY control, compliance and governance GPO to drive standardization across all sectors. Qualifications Bachelor degree in Finance/Supply Chain Management/Accounting/Business Administration. A master degree is a plus 6+ Years of experience required Functional knowledgeDepth of different aspects of Procurement such as processes and tools, knowledge in Food & Beverage industry a plus Experience in sourcing processes and technologies, with experience of implementing them in a global and regional environment Advanced proficiency in data analysis tools, including Microsoft Excel (e.g., advanced formulas, pivot tables, data validation); data visualization tools skills like Tableau or PowerBI is a plus Strong communication & negotiation skills Results Oriented comfortable setting and delivering against bold, stretch targets English essential, both verbal and in writing Comfortable working within matrix organization Affinity with technology applications and business processes and the impact on people Strong analytical, problem solving, and root cause identification skills Solid understanding of the PepsiCo organization and cultural differences Differentiating Competencies Required Decision making Work under pressure Cross functional teamwork skills Collaboration and influence Act with Integrity Experience with large-scale organizational change effort Ability to flex to collaborate with people in different locations of various time zones Ability to translate complex situations into executive level communication

Overview Enterprise Data Operations Analyst Job OverviewAs an Analyst, Data Modeling , your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics . The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks , Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/ modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives , maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ , and Great Expectations. Experience building/ operating highly available , distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake . Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI ).

Overview As Senior Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview As a member of the Platform engineering team, you will be the key techno functional expert leading and overseeing PepsiCo's Platforms & operations and drive a strong vision for how Platforms engineering can proactively create a positive impact on the business. You'll be an empowered Leader of a team of Platform engineers who build Platform products for platform optimization and cost optimization and build tools for Platform ops and Data Ops on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As Leader of the Platform engineering team, you will help in managing platform Governance team that builds frameworks to guardrail the platforms of very large and complex data applications in public cloud environments and directly impact the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Responsibilities Active contributor to cost optimization of platforms and services. Manage and scale Azure Data Platforms to support new product launches and drive Platform Stability and Observability across data products. Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for Data Platforms for cost and performance. Responsible for implementing best practices around systems integration, security, performance and Platform management. Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape. Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions. Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners. Develop and optimize procedures to production Alize data science models. Define and manage SLAs for Platforms and processes running in production. Support large-scale experimentation done by data scientists. Prototype new approaches and build solutions at scale. Research in state-of-the-art methodologies. Create documentation for learnings and knowledge transfer. Create and audit reusable packages or libraries. Qualifications 10+ years of overall technology experience that includes at least 4+ years of hands-on software development, Program management, and Advanced Analytics. 4+ years of experience with Power BI, Tableau, Data Warehousing, and Data Analytics tools. 4+ years of experience in Platform optimization and performance tuning Experience in managing multiple teams and coordinating with different stakeholders to implement the vision of the team. Fluent with Azure cloud services. Azure Certification is a plus. Experience with integration of multi cloud services with on-premises technologies. Experience with data modeling, data warehousing, and building Symantec Models. Proficient in DAX queries, Copilot and AI Skills Experience building/operating highly available, distributed systems of data Visualization . Experience with at least one MPP database technology such as Redshift, Synapse or Snowflake. Experience with version control systems like Github and deployment & CI tools. Knowledge of Azure Data Factory, Azure Databricks. Experience with Statistical/ML techniques is a plus. Experience with building solutions in the retail or in the supply chain space is a plus Understanding of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with Augmented Analytics tools is Plus (such as ThoughtSpot, Tellius).

Overview Enterprise Data Operations Sr Analyst L08 Job OverviewAs Senior Analyst, Data Modeling , your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics . The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks , Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/ modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives , maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ , and Great Expectations. Experience building/ operating highly available , distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake . Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI ). Does the person hired for this job need to be based in a PepsiCo office, or can they be remote Employee must be based in a Pepsico office Primary Work LocationHyderabad HUB-IND

Overview As an Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview As Senior Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Job Title Senior Software EngineerExperience 12-20 YearsLocation Bangalore : Strong knowledge & hands-on experience in AWS Data Bricks Nice to have Worked in hp eco system (FDL architecture) Technically strong to help the team on any technical issues they face during the execution. Owns the end-to-end technical deliverablesHands on data bricks + SQL knowledge Experience in AWS S3, Redshift, EC2 and Lambda services Extensive experience in developing and deploying Bigdata pipelines Experience in Azure data lake Strong hands on in SQL development / Azure SQL and in-depth understanding of optimization and tuning techniques in SQL with Redshift Development in Notebooks (like Jupyter, DataBricks, Zeppelin etc) Development experience in Spark Experience in scripting language like python and any other programming language Roles and Responsibilities Candidate must have hands on experience in AWS Data Databricks Good development experience using Python/Scala, Spark SQL and Data Frames Hands-on with Databricks, Data Lake and SQL knowledge is a must. Performance tuning, troubleshooting, and debugging SparkTM Process Skills: Agile Scrum Qualification: Bachelor of Engineering (Computer background preferred)

Job Title Data ArchitectExperience 10-12 YearsLocation Chennai : 10-12 years experience as Data Architect Strong expertise in streaming data technologies like Apache Kafka, Flink, Spark Streaming, or Kinesis. ProficiencyinprogramminglanguagessuchasPython,Java,Scala,orGo ExperiencewithbigdatatoolslikeHadoop,Hive,anddatawarehousessuchas Snowflake,Redshift,Databricks,MicrosoftFabric. Proficiencyindatabasetechnologies(SQL,NoSQL,PostgreSQL,MongoDB,DynamoDB,YugabyteDB). Should be flexible to work as anIndividual contributor

Job Title:AWS Data EngineerExperience5-10 YearsLocation:Bangalore : Technical Skills: 5 + Years of experience as AWS Data Engineer, AWS S3, Glue Catalog, Glue Crawler, Glue ETL, Athena write Glue ETLs to convert data in AWS RDS for SQL Server and Oracle DB to Parquet format in S3 Execute Glue crawlers to catalog S3 files. Create catalog of S3 files for easier querying Create SQL queries in Athena Define data lifecycle management for S3 files Strong experience in developing, debugging, and optimizing Glue ETL jobs using PySpark or Glue Studio. Ability to connect Glue ETLs with AWS RDS (SQL Server and Oracle) for data extraction and write transformed data into Parquet format in S3. Proficiency in setting up and managing Glue Crawlers to catalog data in S3. Deep understanding of S3 architecture and best practices for storing large datasets. Experience in partitioning and organizing data for efficient querying in S3. Knowledge of Parquet file format advantages for optimized storage and querying. Expertise in creating and managing the AWS Glue Data Catalog to enable structured and schema-aware querying of data in S3. Experience with Amazon Athena for writing complex SQL queries and optimizing query performance. Familiarity with creating views or transformations in Athena for business use cases. Knowledge of securing data in S3 using IAM policies, S3 bucket policies, and KMS encryption. Understanding of regulatory requirements (e.g., GDPR) and implementing secure data handling practices. Non-Technical Skills: Candidate needs to be Good Team Player Effective interpersonal, team building and communication skills. Ability to communicate complex technology to no tech audience in simple and precise manner.

Job Title:SQL, AWS Redshift, PostgreSQLExperience10-15 YearsLocation:Bangalore : SQL, AWS Redshift, PostgreSQL

Job Title:EMR_Spark SMEExperience:5-10 YearsLocation:Bangalore : Technical Skills: 5+ years of experience in big data technologies with hands-on expertise in AWS EMR and Apache Spark. Proficiency in Spark Core, Spark SQL, and Spark Streaming for large-scale data processing. Strong experience with data formats (Parquet, Avro, JSON) and data storage solutions (Amazon S3, HDFS). Solid understanding of distributed systems architecture and cluster resource management (YARN). Familiarity with AWS services (S3, IAM, Lambda, Glue, Redshift, Athena). Experience in scripting and programming languages such as Python, Scala, and Java. Knowledge of containerization and orchestration (Docker, Kubernetes) is a plus. Architect and develop scalable data processing solutions using AWS EMR and Apache Spark. Optimize and tune Spark jobs for performance and cost efficiency on EMR clusters. Monitor, troubleshoot, and resolve issues related to EMR and Spark workloads. Implement best practices for cluster management, data partitioning, and job execution. Collaborate with data engineering and analytics teams to integrate Spark solutions with broader data ecosystems (S3, RDS, Redshift, Glue, etc.). Automate deployments and cluster management using infrastructure-as-code tools like CloudFormation, Terraform, and CI/CD pipelines. Ensure data security and governance in EMR and Spark environments in compliance with company policies. Provide technical leadership and mentorship to junior engineers and data analysts. Stay current with new AWS EMR features and Spark versions to recommend improvements and upgrades. Requirements and Skills Performance tuning and optimization of Spark jobs. Problem-solving skills with the ability to diagnose and resolve complex technical issues. Strong experience with version control systems (Git) and CI/CD pipelines. Excellent communication skills to explain technical concepts to both technical and non-technical audiences. Qualification: Education qualificationB.Tech, BE, BCA, MCA, M. Tech or equivalent technical degree from a reputed college. Certifications: AWS Certified Solutions Architect Associate/Professional AWS Certified Data Analytics Specialty

Design, implement, and maintain data pipelines for processing large datasets, ensuring data availability, quality, and efficiency for machine learning model training and inference. Collaborate with data scientists to streamline the deployment of machine learning models, ensuring scalability, performance, and reliability in production environments. Develop and optimize ETL (Extract, Transform, Load) processes, ensuring data flow from various sources into structured data storage systems. Automate ML workflows using ML Ops tools and frameworks (e.g., Kubeflow, MLflow, TensorFlow Extended (TFX)). Ensure effective model monitoring, versioning, and logging to track performance and metrics in a production setting. Collaborate with cross-functional teams to improve data architectures and facilitate the continuous integration and deployment of ML models. Work on data storage solutions, including databases, data lakes, and cloud-based storage systems (e.g., AWS, GCP, Azure). Ensure data security, integrity, and compliance with data governance policies. Perform troubleshooting and root cause analysis on production-level machine learning systems. Skills: Glue, Pyspark, AWS Services, Strong in SQL; Nice to have : Redshift, Knowledge of SAS Dataset Mandatory Competencies DevOps - CLOUD AWS DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Docker ETL - ETL - AWS Glue Big Data - Big Data - Pyspark Database - Other Databases - Redshift Data Science and Machine Learning - Data Science and Machine Learning - Azure ML Beh - Communication and collaboration DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Containerization (Docker, Kubernetes) Database - Sql Server - SQL Packages Cloud - Azure - Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage, Event Hubs, HDInsight DevOps/Configuration Mgmt - Cloud Platforms - AWS

Job Title: Data Associate - Cloud Data Engineering Experience: 4+ Years Employment Type: Full-Time Industry: Information Technology / Data Engineering / Cloud Platforms Job Summary: We are seeking a highly skilled and experienced Senior Data Associate to join our data engineering team. The ideal candidate will have a strong background in cloud data platforms, big data processing, and enterprise data systems, with hands-on experience across both AWS and Azure ecosystems. This role involves building and optimizing data pipelines, managing large-scale data lakes and warehouses, and enabling advanced analytics and reporting. Key Responsibilities: Design, develop, and maintain scalable data pipelines using AWS Glue, PySpark, and Azure Data Factory. Work with AWS Redshift, Athena, Azure Synapse, and Databricks to support data warehousing and analytics solutions. Integrate and manage data across MongoDB, Oracle, and cloud-native storage like Azure Data Lake and S3. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality datasets. Implement data quality checks, monitoring, and governance practices. Optimize data workflows for performance, scalability, and cost-efficiency. Support data migration and modernization initiatives across cloud platforms. Document data flows, architecture, and technical specifications. Required Skills & Qualifications: 8+ years of experience in data engineering, data integration, or related roles. Strong hands-on experience with: AWS Redshift, Athena, Glue, S3 Azure Data Lake, Synapse Analytics, Databricks PySpark for distributed data processing MongoDB and Oracle databases Proficiency in SQL, Python, and data modeling. Experience with ETL/ELT design and implementation. Familiarity with data governance, security, and compliance standards. Strong problem-solving and communication skills. Preferred Qualifications: Certifications in AWS (e.g., Data Analytics Specialty) or Azure (e.g., Azure Data Engineer Associate). Experience with CI/CD pipelines and DevOps for data workflows. Knowledge of data cataloging tools (e.g., AWS Glue Data Catalog, Azure Purview). Exposure to real-time data processing and streaming technologies. Required Skills Azure,AWS REDSHIFT,Athena,Azure Data Lake

We are seeking a highly skilled Senior Marketing Data Analyst to join our team. This role will involve analyzing and interpreting marketing data to identify trends, patterns, and actionable insights. About the Role The successful candidate will be responsible for: Analyzing marketing data to support campaign targeting and optimize marketing efforts. C ollaborating with cross-functional teams to understand data needs and provide analytical solutions. Evaluating marketing campaign performance and providing recommendations for improvement. Ensuring data quality and accuracy through validation and cleanup. Conducting ad-hoc analysis to solve business problems and provide actionable insights. Requirements To be successful in this role, you will need: A minimum of 3 years of experience in data analysis. Proficiency in SQL, Snowflake, and Python on a daily basis. Ability to work with cross-functional teams and create relevant insights.

8+ years of experience in data engineering with a strong focus on AWS services . Proven expertise in: Amazon S3 for scalable data storage AWS Glue for ETL and serverless data integration using Amazon S3, DataSync, EMR, Redshift for data warehousing and analytics Proficiency in SQL , Python , or PySpark for data processing. Experience with data modeling , partitioning strategies , and performance optimization . Familiarity with orchestration tools like AWS Step Functions , Apache Airflow , or Glue Workflows . Strong understanding of data lake and data warehouse architectures. Excellent problem-solving and communication skills. Mandatory Competencies Beh - Communication ETL - ETL - AWS Glue Big Data - Big Data - Pyspark Cloud - AWS - AWS S3, S3 glacier, AWS EBS Cloud - AWS - Tensorflow on AWS, AWS Glue, AWS EMR, Amazon Data Pipeline, AWS Redshift Database - Database Programming - SQL Programming Language - Python - Python Shell Cloud - Azure - Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage, Event Hubs, HDInsight

Job description Data Engineer III/ IV - IN Work Location - Remote Job Description Summary The Data engineer is responsible for managing and operating upon Databricks, Dbt, SSRS, SSIS, AWS DWS, AWS APP Flow, PowerBI/Tableau. The engineer will work closely with the customer and team to manage and operate cloud data platform. Job Description Provides Level 3/4 operational coverage: Troubleshooting incident/problem, includes collecting logs, cross-checking against known issues, investigate common root causes (for example failed batches, infra related items such as connectivity to source, network issues etc.) Knowledge Management: Create/update runbooks as needed / Entitlements Governance: Watch all the configuration changes to batches and infrastructure (cloud platform) along with mapping it with proper documentation and aligning resources. Communication: Lead and act as a POC for customer from off-site, handling communication, escalation, isolating issues and coordinating with off-site resources while level setting expectation across stakeholders Change Management: Align resources for on-demand changes and coordinate with stakeholders as required Request Management: Handle user requests if the request is not runbook-based create a new KB or update runbook accordingly Incident Management and Problem Management, Root cause Analysis, coming up with preventive measures and recommendations such as enhancing monitoring or systematic changes as needed. KNOWLEDGE/SKILLS/ABILITY Good hands-on Databricks, Dbt, SSRS, SSIS, AWS DWS, AWS APP Flow, PowerBI/Tableau. Ability to read and write sql and stored procedures. Good hands-on experience in configuring, managing and troubleshooting along with general analytical and problem-solving skills. Excellent written and verbal communication skills. Ability to communicate technical info and ideas so others will understand. Ability to successfully work and promote inclusiveness in small groups. JOB COMPLEXITY: This role requires extensive problem-solving skills and the ability to research an issue, determine the root cause, and implement the resolution; research of various sources such as databricks/AWS/tableau documentation that may be required to identify and resolve issues. Must have the ability to prioritize issues and multi-task. EXPERIENCE/EDUCATION Requires a Bachelors degree in computer science or other related field plus 8+ years of hands-on experience in configuring and managing AWS/tableau and databricks solution. Experience with Databricks and tableau environment is desired. "Remote postings are limited to candidates residing within the country specified in the posting location" About Rackspace Technology We are the multicloud solutions experts. We combine our expertise with the worlds leading technologies across applications, data and security — to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future. More on Rackspace Technology Though we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic.

Key Result Areas and Activities: Design and Development: Design, implement, and manage Redshift clusters for high availability, performance, and security. Performance Optimization: Monitor and optimize database performance, including query tuning and resource management. Backup and Recovery: Develop and maintain database backup and recovery strategies. Security Enforcement: Implement and enforce database security policies and procedures. Cost-Performance Balance: Ensure an optimal balance between cost and performance. Collaboration with Development Teams: Work with development teams to design and optimize database schemas and queries. Perform database migrations, upgrades, and patching. Issue Resolution: Troubleshoot and resolve database-related issues, providing support to development and operations teams. Automate routine database tasks using scripting languages and tools. Must-Have: Strong understanding of database design, performance tuning, and optimization techniques Proficiency in SQL and experience with database scripting languages (e.g., Python, Shell) Experience with database backup and recovery, security, and high availability solutions Familiarity with AWS services and tools, including S3, EC2, IAM, and CloudWatch Operating System - Any flavor of Linux, Windows Core Redshift Administration Skills -Cluster Management, Performance Optimization, workload management (WLM), vacuuming/analyzing tables for optimal performance, IAM policies, role[1]based access control, Backup & Recovery, automated backups, and restoration strategies. SQL Query Optimization, distribution keys, sort keys, and compression encoding Knowledge of COPY and UNLOAD commands, S3 integration, and best practices for bulk data loading Scripting & Automation for automating routine DBA tasks Expertise in debugging slow queries, troubleshooting system tables

Responsibilities Data Architecture: Develop and maintain the overall data architecture, ensuring scalability, performance, and data quality. AWS Data Services: Expertise in using AWS data services such as AWS Glue, S3, SNS, SES, Dynamo DB, Redshift, Cloud formation, Cloud watch, IAM, DMS, Event bridge scheduler etc. Data Warehousing: Design and implement data warehouses on AWS, leveraging AWS Redshift or other suitable options. Data Lakes: Build and manage data lakes on AWS using AWS S3 and other relevant services. Data Pipelines: Design and develop efficient data pipelines to extract, transform, and load data from various sources. Data Quality: Implement data quality frameworks and best practices to ensure data accuracy, completeness, and consistency. Cloud Optimization: Optimize data engineering solutions for performance, cost-efficiency, and scalability on the AWS cloud. Team Leadership: Mentor and guide data engineers, ensuring they adhere to best practices and meet project deadlines. Qualifications Bachelors degree in computer science, Engineering, or a related field. 6-7 years of experience in data engineering roles, with a focus on AWS cloud platforms. Strong understanding of data warehousing and data lake concepts. Proficiency in SQL and at least one programming language ( Python/Pyspark ). Good to have - Experience with any big data technologies like Hadoop, Spark, and Kafka. Knowledge of data modeling and data quality best practices. Excellent problem-solving, analytical, and communication skills. Ability to work independently and as part of a team. Preferred Qualifications Certifications in AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect - Data. Mandatory Competencies Big Data - Big Data - Pyspark Data on Cloud - Azure Data Lake (ADL) Beh - Communication and collaboration Cloud - AWS - AWS Lambda,AWS EventBridge, AWS Fargate Cloud - AWS - AWS S3, S3 glacier, AWS EBS Cloud - Azure - Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage, Event Hubs, HDInsight Cloud - AWS - Tensorflow on AWS, AWS Glue, AWS EMR, Amazon Data Pipeline, AWS Redshift Database - Sql Server - SQL Packages Data Science and Machine Learning - Data Science and Machine Learning - Python

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Our global in-house technology team of more than 5,000 of engineers, data scientists, architects, coaches and product managers strive to make Target the most convenient, safe and joyful place to shop. We use agile practices and leverage open-source software to adapt and build best-in-class technology for our team members and guestsand we do so with a focus on diversity and inclusion, experimentation and continuous learning. Pyramid Overview Our Product Engineering teams fuel Targets business with cutting-edge technology to deliver incredible experiences and value for guests and team members. Using a responsive architecture platform, we build and deploy industry-leading technology enabling Target to operate efficiently, securely, and reliably from the inside out. We work across Target, developing comprehensive product strategies, leveraging enterprise and guest feedback to set the standard for best in retail. Position Overview 4+ years of experience in software design & development with 3+ years of experience in building scalable backend applications using Java Demonstrates broad and deep expertise in Java/Kotlin and frameworks. Designs, develops, and approves end-to-end functionality of a product line, platform, or infrastructure. Communicates and coordinates with project team, partners, and stakeholders. Demonstrates expertise in analysis and optimization of systems capacity, performance, and operational health. Maintains deep technical knowledge within areas of expertise. Stays current with new and evolving technologies via formal training and self-directed education. Experience integrating with third party and opensource frameworks. About You 4 year degree or equivalent experience Experience4 -7 years Programming experience with Java - Springboot & Kotlin - micronaut Strong problem-solving skills with a good understanding of data structures and algorithms. Must have exposure to non-relational databases like MongoDB. Must have exposure to distributed systems and microservice architecture. Good to Have exposure to Data Pipeline, ML Ops, Spark, Python Demonstrates a solid understanding of the impact of own work on the team and/or guests Writes and organizes code using multiple computer languages, including distributed programming and understand different frameworks and paradigm Delivers high-performance, scalable, repeatable, and secure deliverables with broad impact (high throughput and low latency) Influences and applies data standards, policies, and procedures Maintains technical knowledge within areas of expertise Stays current with new and evolving technologies via formal training and self-directed education. Know More Here: Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Follow us on social media https://www.linkedin.com/company/target/ Target Tech- https://tech.target.com/ Target in india Belonging

Responsibilities Data Architecture: Develop and maintain the overall data architecture, ensuring scalability, performance, and data quality. AWS Data Services: Expertise in using AWS data services such as AWS Glue, S3, SNS, SES, Dynamo DB, Redshift, Cloud formation, Cloud watch, IAM, DMS, Event bridge scheduler etc. Data Warehousing: Design and implement data warehouses on AWS, leveraging AWS Redshift or other suitable options. Data Lakes: Build and manage data lakes on AWS using AWS S3 and other relevant services. Data Pipelines: Design and develop efficient data pipelines to extract, transform, and load data from various sources. Data Quality: Implement data quality frameworks and best practices to ensure data accuracy, completeness, and consistency. Cloud Optimization: Optimize data engineering solutions for performance, cost-efficiency, and scalability on the AWS cloud. Qualifications Bachelors degree in computer science, Engineering, or a related field. 4-5 years of experience in data engineering roles, with a focus on AWS cloud platforms. Strong understanding of data warehousing and data lake concepts. Proficiency in SQL and at least one programming language ( Python/Pyspark ). Good to have - Experience with any big data technologies like Hadoop, Spark, and Kafka. Knowledge of data modeling and data quality best practices. Excellent problem-solving, analytical, and communication skills. Ability to work independently and as part of a team. Preferred Qualifications Certifications in AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect - Data. Mandatory Competencies Big Data - Big Data - Pyspark Beh - Communication and collaboration Cloud - AWS - AWS Lambda,AWS EventBridge, AWS Fargate Database - Sql Server - SQL Packages Data Science and Machine Learning - Data Science and Machine Learning - Python