1356 Bigquery Jobs - Page 10

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. Required Skills & Experience: Experience: 8-10 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies Database - PostgreSQL - PostgreSQL Database - Sql Server - SQL Packages ETL - ETL - Tester QA/QE - QA Automation - ETL Testing Beh - Communication

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. ________________________________________ Required Skills & Experience: Experience: 5-8 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies QA/QE - QA Automation - ETL Testing ETL - ETL - Tester Beh - Communication and collaboration Database - Sql Server - SQL Packages Database - PostgreSQL - PostgreSQL

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. Required Skills & Experience: Experience: 5-8 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies QA/QE - QA Automation - ETL Testing ETL - ETL - Tester Beh - Communication and collaboration Database - Sql Server - SQL Packages Database - PostgreSQL - PostgreSQL

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. Required Skills & Experience: Experience : 5-8 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies QA/QE - QA Automation - ETL Testing ETL - ETL - Tester Beh - Communication and collaboration Database - Sql Server - SQL Packages Database - PostgreSQL - PostgreSQL

Job Description: Senior Data Analyst Location: Hyderabad, IN - Work from Office Experience: 7+ Years Role Summary We are seeking an experienced and highly skilled Senior Data Analyst to join our team. The ideal candidate will possess a deep proficiency in SQL, a strong understanding of data architecture, and a working knowledge of the Google Cloud platform (GCP)based ecosystem. They will be responsible for turning complex business questions into actionable insights, driving strategic decisions, and helping shape the future of our Product/Operations team. This role requires a blend of technical expertise, analytical rigor, and excellent communication skills to partner effectively with engineering, product, and business leaders. Key Responsibilities Advanced Data Analysis: Utilize advanced SQL skills to query, analyze, and manipulate large, complex datasets. Develop and maintain robust, scalable dashboards and reports to monitor key performance indicators (KPIs). Source Code management : Proven ability to effectively manage, version, and collaborate on code using codebase management systems like GitHub. Responsible for upholding data integrity, producing reproducible analyses, and fostering a collaborative database management environment through best practices in version control and code documentation. Strategic Insights: Partner with product managers and business stakeholders to define and answer critical business questions. Conduct deep-dive analyses to identify trends, opportunities, and root causes of performance changes. Data Architecture & Management: Work closely with data engineers to design, maintain, and optimize data schemas and pipelines. Provide guidance on data modeling best practices and ensure data integrity and quality. Reporting & Communication: Translate complex data findings into clear, concise, and compelling narratives for both technical and non-technical audiences. Present insights and recommendations to senior leadership to influence strategic decision-making. Project Leadership: Lead analytical projects from end to end, including defining project scope, methodology, and deliverables. Mentor junior analysts, fostering a culture of curiosity and data-driven problem-solving. Required Skills & Experience Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or a related discipline. 5+ years of professional experience in a data analysis or business intelligence role. Expert-level proficiency in SQL with a proven ability to write complex queries, perform window functions, and optimize queries for performance on massive datasets. Strong understanding of data architecture, including data warehousing, data modeling (e.g., star/snowflake schemas), and ETL/ELT principles. Excellent communication and interpersonal skills, with a track record of successfully influencing stakeholders. Experience with a business intelligence tool such as Tableau, Looker, or Power BI to create dashboards and visualizations. Experience with internal Google/Alphabet data tools and infrastructure, such as BigQuery, Dremel, or Google-internal data portals. Experience with statistical analysis, A/B testing, and experimental design. Familiarity with machine learning concepts and their application in a business context. A strong sense of curiosity and a passion for finding and communicating insights from data. Proficiency with scripting languages for data analysis (e.g., App scripting , Python or R ) would be an added advantage Responsibilities Lead a team of data scientists and analysts to deliver data-driven insights and solutions. Oversee the development and implementation of data models and algorithms to support new product development. Provide strategic direction for data science projects ensuring alignment with business goals. Collaborate with cross-functional teams to integrate data science solutions into business processes. Analyze complex datasets to identify trends and patterns that inform business decisions. Utilize generative AI techniques to develop innovative solutions for product development. Ensure adherence to ITIL V4 practices in all data science projects. Develop and maintain documentation for data science processes and methodologies. Mentor and guide team members to enhance their technical and analytical skills. Monitor project progress and adjust strategies to meet deadlines and objectives. Communicate findings and recommendations to stakeholders in a clear and concise manner. Drive continuous improvement in data science practices and methodologies. Foster a culture of innovation and collaboration within the data science team. Qualifications Possess strong experience in business analysis and data analysis. Demonstrate expertise in generative AI and its applications in product development. Have a solid understanding of ITIL V4 practices and their implementation. Exhibit excellent communication and collaboration skills. Show proficiency in managing and leading a team of data professionals. Display a commitment to working from the office during day shifts.

Role Description Provides leadership for the overall architecture, design, development, and deployment of a full-stack cloud native data analytics platform. Designing & Augmenting Solution architecture for Data Ingestion, Data Preparation, Data Transformation, Data Load, ML & Simulation Modelling, Java BE & FE, State Machine, API Management & Intelligence consumption using data products, on cloud Understand Business Requirements and help in developing High level and Low-level Data Engineering and Data Processing Documentation for the cloud native architecture Developing conceptual, logical and physical target-state architecture, engineering and operational specs. Work with the customer, users, technical architects, and application designers to define the solution requirements and structure for the platform Model and design the application data structure, storage, and integration Lead the database analysis, design, and build effort Work with the application architects and designers to design the integration solution Ensure that the database designs fulfill the requirements, including data volume, frequency needs, and long-term data growth Able to perform Data Engineering tasks using Spark Knowledge of developing efficient frameworks for development and testing using (Sqoop/Nifi/Kafka/Spark/Streaming/ WebHDFS/Python) to enable seamless data ingestion processes on to the Hadoop/BigQuery platforms. Enabling Data Governance and Data Discovery Exposure of Job Monitoring framework along validations automation Exposure of handling structured, Un Structured and Streaming data. Technical Skills Experience with building data platform on cloud (Data Lake, Data Warehouse environment, Databricks) Strong technical understanding of data modeling, design and architecture principles and techniques across master data, transaction data and derived/analytic data Proven background of designing and implementing architectural solutions which solve strategic and tactical business needs Deep knowledge of best practices through relevant experience across data-related disciplines and technologies, particularly for enterprise-wide data architectures, data management, data governance and data warehousing Highly competent with database design Highly competent with data modeling Strong Data Warehousing and Business Intelligence skills or including: Handling ELT and scalability issues for enterprise level data warehouse Creating ETLs/ELTs to handle data from various data sources and various formats Strong hands-on experience of programming language like Python, Scala with Spark and Beam. Solid hands-on and Solution Architecting experience in Cloud Technologies Aws, Azure and GCP (GCP preferred) Hands on working experience of data processing at scale with event driven systems, message queues (Kafka/ Flink/Spark Streaming) Hands on working Experience with GCP Services like BigQuery, DataProc, PubSub, Dataflow, Cloud Composer, API Gateway, Datalake, BigTable, Spark, Apache Beam, Feature Engineering/Data Processing to be used for Model development Experience gathering and processing raw data at scale (including writing scripts, web scraping, calling APIs, write SQL queries, etc.) Experience building data pipelines for structured/unstructured, real-time/batch, events/synchronous/ asynchronous using MQ, Kafka, Steam processing Hands-on working experience in analyzing source system data and data flows, working with structured and unstructured data Must be very strong in writing SparkSQL queries Strong organizational skills, with the ability to work autonomously as well as leading a team Pleasant Personality, Strong Communication & Interpersonal Skills Qualifications A bachelor's degree in computer science, computer engineering, or a related discipline is required to work as a technical lead Certification in GCP would be a big plus Individuals in this field can further display their leadership skills by completing the Project Management Professional certification offered by the Project Management Institute.

Your Role We are hiring a GCP Kubernetes Engineer with 912 years of experience. Ideal candidates should have strong expertise in cloud-native technologies, container orchestration, and infrastructure automation. This is a Pan India opportunity offering flexibility and growth. Join us to build scalable, secure, and innovative cloud solutions across diverse industries. Design, implement, and manage scalable, highly available systems on Google Cloud Platform (GCP). Work with GCP IaaS componentsCompute Engine, VPC, VPN, Cloud Interconnect, Load Balancing, Cloud CDN, Cloud Storage, and Backup/DR solutions. Utilize GCP PaaS servicesCloud SQL, App Engine, Cloud Functions, Pub/Sub, Firestore/Cloud Spanner, and Dataflow. Deploy and manage containerized applications using Google Kubernetes Engine (GKE), Helm charts, and Kubernetes tooling. Automate infrastructure provisioning using gcloud CLI, Deployment Manager, or Terraform. Implement CI/CD pipelines using Cloud Build for automated deployments. Monitor infrastructure and applications using Cloud Monitoring, Logging, and related tools. Manage IAM, VPC Service Controls, Cloud Armor, and Security Command Center. Troubleshoot and resolve complex infrastructure and application issues. Your Profile 6+ years of cloud engineering experience with a strong focus on GCP. Proven hands-on expertise in GCP IaaS, PaaS, and GKE. Experience with monitoring, logging, and automation tools in GCP. Strong problem-solving, analytical, and communication skills. What you"ll love about working here You can shape yourcareer with us. We offer a range of career paths and internal opportunities within Capgemini group. You will also get personalized career guidance from our leaders. You will get comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage or new parent support via flexible work. At Capgemini, you can work oncutting-edge projects in tech and engineering with industry leaders or createsolutions to overcome societal and environmental challenges.

Looking for smart, curious and highly motivated engineers from an Application Support or Test Automation background, who have good experience in Python and SDLC . The ideal candidate who has the desire to work on Gen AI projects would have enrolled themselves in some Gen AI courses, and should have done some reading/exploration by themselves. The ideal candidate should have 4-10 years of practical work experience in areas like - integrating/managing APIs, async programming frameworks/libraries, state management , concurrency , containerization and telemetry. Mandatory Competencies Data Science and Machine Learning - Data Science and Machine Learning - Gen AI Python - Python UI - Typescript Beh - Communication

" PLEASE READ THE JOB DESTCRIPTION AND APPLY" Data Engineer Job Description Position Overview Yesterday is history, tomorrow is a mystery, but today is a gift. That's why we call it the present. - Master Oogway Join CustomerLabs' dynamic data team as a Data Engineer and play a pivotal role in transforming raw marketing data into actionable insights that power our digital marketing platform. As a key member of our data infrastructure team, you will design, develop, and maintain robust data pipelines, data warehouses, and analytics platforms that serve as the backbone of our digital marketing product development. Sometimes the hardest choices require the strongest wills. - Thanos (but we promise, our data decisions are much easier! ) In this role, you will collaborate with cross-functional teams including Data Scientists, Product Managers, and Marketing Technology specialists to ensure seamless data flow from various marketing channels, ad platforms, and customer touchpoints to our analytics dashboards and reporting systems. You'll be responsible for building scalable, reliable, and efficient data solutions that can handle high-volume marketing data processing and real-time campaign analytics. What You'll Do: - Design and implement enterprise-grade data pipelines for marketing data ingestion and processing - Build and optimize data warehouses and data lakes to support digital marketing analytics - Ensure data quality, security, and compliance across all marketing data systems - Create data models and schemas that support marketing attribution, customer journey analysis, and campaign performance tracking - Develop monitoring and alerting systems to maintain data pipeline reliability for critical marketing operations - Collaborate with product teams to understand digital marketing requirements and translate them into technical solutions Why This Role Matters: I can do this all day. - Captain America (and you'll want to, because this role is that rewarding!) You'll be the backbone behind the data infrastructure that powers CustomerLabs' digital marketing platform, making marketers' lives easier and better. Your work directly translates to smarter automation, clearer insights, and more successful campaigns - helping marketers focus on what they do best while we handle the complex data heavy lifting. Sometimes you gotta run before you can walk. - Iron Man (and sometimes you gotta build the data pipeline before you can analyze the data! ) Our Philosophy: We believe in the power of data to transform lives, just like the Dragon Warrior transformed the Valley of Peace. Every line of code you write, every pipeline you build, and every insight you enable has the potential to change how marketers work and succeed. We're not just building data systems - we're building the future of digital marketing, one insight at a time. Your story may not have such a happy beginning, but that doesn't make you who you are. It is the rest of your story, who you choose to be. - Soothsayer What Makes You Special: We're looking for someone who embodies the spirit of both Captain America's unwavering dedication and Iron Man's innovative genius. You'll need the patience to build robust systems (like Cap's shield ) and the creativity to solve complex problems (like Tony's suit). Most importantly, you'll have the heart to make a real difference in marketers' lives. Inner peace... Inner peace... Inner peace... - Po (because we know data engineering can be challenging, but we've got your back! ) Key Responsibilities Data Pipeline Development - Design, build, and maintain robust, scalable data pipelines and ETL/ELT processes - Develop data ingestion frameworks to collect data from various sources (databases, APIs, files, streaming sources) - Implement data transformation and cleaning processes to ensure data quality and consistency - Optimize data pipeline performance and reliability Data Infrastructure Management - Design and implement data warehouse architectures - Manage and optimize database systems (SQL and NoSQL) - Implement data lake solutions and data governance frameworks - Ensure data security, privacy, and compliance with regulatory requirements Data Modeling and Architecture - Design and implement data models for analytics and reporting - Create and maintain data dictionaries and documentation - Develop data schemas and database structures - Implement data versioning and lineage tracking Data Quality, Security, and Compliance - Ensure data quality, integrity, and consistency across all marketing data systems - Implement and monitor data security measures to protect sensitive information - Ensure privacy and compliance with regulatory requirements (e.g., GDPR, CCPA) - Develop and enforce data governance policies and best practices Collaboration and Support - Work closely with Data Scientists, Analysts, and Business stakeholders - Provide technical support for data-related issues and queries Monitoring and Maintenance - Implement monitoring and alerting systems for data pipelines - Perform regular maintenance and optimization of data systems - Troubleshoot and resolve data pipeline issues - Conduct performance tuning and capacity planning Required Qualifications Experience - 2+ years of experience in data engineering or related roles - Proven experience with ETL/ELT pipeline development - Experience with cloud data platform (GCP) - Experience with big data technologies Technical Skills - Programming Languages : Python, SQL, Golang (preferred) - Databases: PostgreSQL, MySQL, Redis - Big Data Tools: Apache Spark, Apache Kafka, Apache Airflow, DBT, Dataform - Cloud Platforms: GCP (BigQuery, Dataflow, Cloud run, Cloud SQL, Cloud Storage, Pub/Sub, App Engine, Compute Engine etc.) - Data Warehousing: Google BigQuery - Data Visualization: Superset, Looker, Metabase, Tableau - Version Control: Git, GitHub - Containerization: Docker Soft Skills - Strong problem-solving and analytical thinking - Excellent communication and collaboration skills - Ability to work independently and in team environments - Strong attention to detail and data quality - Continuous learning mindset Preferred Qualifications Additional Experience - Experience with real-time data processing and streaming - Knowledge of machine learning pipelines and MLOps - Experience with data governance and data catalog tools - Familiarity with business intelligence tools (Tableau, Power BI, Looker, etc.) - Experience using AI-powered tools (such as Cursor, Claude, Copilot, ChatGPT, Gemini, etc.) to accelerate coding, automate tasks, or assist in system design ( We belive run with machine, not against machine ) Interview Process 1. Initial Screening: Phone/video call with HR 2. Technical Interview: Deep dive into data engineering concepts 3. Final Interview: Discussion with senior leadership Note: This job description is intended to provide a general overview of the position and may be modified based on organizational needs and candidate qualifications. Our Team Culture We are Groot. - We work together, we grow together, we succeed together. We believe in: - Innovation First - Like Iron Man, we're always pushing the boundaries of what's possible - Team Over Individual - Like the Avengers, we're stronger together than apart - Continuous Learning - Like Po learning Kung Fu, we're always evolving and improving - Making a Difference - Like Captain America, we fight for what's right (in this case, better marketing!) Growth Journey There is no charge for awesomeness... or attractiveness. - Po Your journey with us will be like Po's transformation from noodle maker to Dragon Warrior: - Level 1 : Master the basics of our data infrastructure - Level 2: Build and optimize data pipelines - Level 3 : Lead complex data projects and mentor others - Level 4: Become a data engineering legend (with your own theme music! ) What We Promise I am Iron Man. - We promise you'll feel like a superhero every day! - Work that matters - Every pipeline you build helps real marketers succeed - Growth opportunities - Learn new technologies and advance your career - Supportive team - We've got your back, just like the Avengers - Work-life balance - Because even superheroes need rest!