242 Oozie Jobs - Page 5

Degree, Post graduate in Computer Science or related field (or equivalent industry experience) Minimum 4+ years of development and design experience in Informatica Big Data Management Extensive knowledge on Oozie scheduling, HQL, Hive, HDFS (including usage of storage controllers) and data partitioning Extensive experience working with SQL and NoSQL databases Linux OS configuration and use, including shell scripting. Good hands on experience with design patterns and their implementation. Well versed with Agile, DevOps and CI/CD principles (GitHub, Jenkins etc.), and actively involved in solving, troubleshooting issues in distributed services ecosystem Familiar with Distributed services resiliency and monitoring in a production environment. Experience in designing, building, testing and implementing security systems including identifying security design gaps in existing and proposed architectures and recommend changes or enhancements. Responsible for adhering to established policies, following best practices, developing and possessing an in-depth understanding of exploits and vulnerabilities, resolving issues by taking the appropriate corrective action. Knowledge on security controls designing Source and Data Transfers including CRON, ETLs, and JDBC ODBC scripts. Understand basics of Networking including DNS, Proxy, ACL, Policy and troubleshooting High level knowledge of compliance and regulatory requirements of data including but not limited to encryption, anonymization, data integrity, policy control features in large scale infrastructures Understand data sensitivity in terms of logging, events and in memory data storage such as no card numbers or personally identifiable data in logs. Implements wrapper solutions for new/existing components with no/minimal security controls to ensure compliance to bank standards. Experience in Agile methodology. Ensure quality of technical and application architecture and design of systems across the organization. Effectively research and benchmark technology against other best in class technologies. Experience in Banking, Financial and Fintech experience in an enterprise environment preferred Able to influence multiple teams on technical considerations, increasing their productivity and effectiveness, by sharing deep knowledge and experience. Self-motivator and self-starter, Ability to own and drive things without supervision and works collaboratively with the teams across the organization. Have excellent soft and interpersonal skills to interact and present the ideas to team. The engineer shouldve good listening skills and speaks clearly in front of team, stakeholders and management. The engineer should always carry positive attitude towards work and establishes effective team relations and builds a climate of trust within the team. Should be enthusiastic and passionate and creates a motivating environment for the team.

About the Role We are seeking a highly skilled Data Engineer with deep expertise in PySpark and the Cloudera Data Platform (CDP) to join our data engineering team. As a Data Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines that ensure high data quality and availability across the organization. This role requires a strong background in big data ecosystems, cloud-native tools, and advanced data processing techniques. The ideal candidate has hands-on experience with data ingestion, transformation, and optimization on the Cloudera Data Platform, along with a proven track record of implementing data engineering best practices. You will work closely with other data engineers to build solutions that drive impactful business insights. Responsibilities Data Pipeline DevelopmentDesign, develop, and maintain highly scalable and optimized ETL pipelines using PySpark on the Cloudera Data Platform, ensuring data integrity and accuracy. Data IngestionImplement and manage data ingestion processes from a variety of sources (e.g., relational databases, APIs, file systems) to the data lake or data warehouse on CDP. Data Transformation and ProcessingUse PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements. Performance OptimizationConduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes. Data Quality and ValidationImplement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline. Automation and OrchestrationAutomate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem. Education and Experience Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field. 3+ years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform. Technical Skills PySparkAdvanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques. Cloudera Data PlatformStrong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase. Data WarehousingKnowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala). Big Data TechnologiesFamiliarity with Hadoop, Kafka, and other distributed computing tools. Orchestration and SchedulingExperience with Apache Oozie, Airflow, or similar orchestration frameworks. Scripting and AutomationStrong scripting skills in Linux.

We are looking for a PySpark solutions developer and data engineer who can design and build solutions for one of our Fortune 500 Client programs, which aims towards building a data standardized and curation needs on Hadoop cluster. This is high visibility, fast-paced key initiative will integrate data across internal and external sources, provide analytical insights, and integrate with the customers critical systems. Key Responsibilities Ability to design, build and unit test applications on Spark framework on Python. Build PySpark based applications for both batch and streaming requirements, which will require in-depth knowledge on majority of Hadoop and NoSQL databases as well. Develop and execute data pipeline testing processes and validate business rules and policies. Optimize performance of the built Spark applications in Hadoop using configurations around Spark Context, Spark-SQL, Data Frame, and Pair RDD's. Optimize performance for data access requirements by choosing the appropriate native Hadoop file formats (Avro, Parquet, ORC etc) and compression codec respectively. Build integrated solutions leveraging Unix shell scripting, RDBMS, Hive, HDFS File System, HDFS File Types, HDFS compression codec. Build data tokenization libraries and integrate with Hive & Spark for column-level obfuscation. Experience in processing large amounts of structured and unstructured data, including integrating data from multiple sources. Create and maintain integration and regression testing framework on Jenkins integrated with Bit Bucket and/or GIT repositories. Participate in the agile development process, and document and communicate issues and bugs relative to data standards in scrum meetings. Work collaboratively with onsite and offshore team. Develop & review technical documentation for artifacts delivered. Ability to solve complex data-driven scenarios and triage towards defects and production issues. Ability to learn-unlearn-relearn concepts with an open and analytical mindset. Participate in code release and production deployment. Challenge and inspire team members to achieve business results in a fast paced and quickly changing environment. Preferred Qualifications BE/B.Tech/ B.Sc. in Computer Science/ Statistics from an accredited college or university. Minimum 3 years of extensive experience in design, build and deployment of PySpark-based applications. Expertise in handling complex large-scale Big Data environments preferably (20Tb+). Minimum 3 years of experience in the followingHIVE, YARN, HDFS. Hands-on experience writing complex SQL queries, exporting, and importing large amounts of data using utilities. Ability to build abstracted, modularized reusable code components. Prior experience on ETL tools preferably Informatica PowerCenter is advantageous. Able to quickly adapt and learn. Able to jump into an ambiguous situation and take the lead on resolution. Able to communicate and coordinate across various teams. Are comfortable tackling new challenges and new ways of working Are ready to move from traditional methods and adapt into agile ones Comfortable challenging your peers and leadership team. Can prove yourself quickly and decisively. Excellent communication skills and Good Customer Centricity. Strong Target & High Solution Orientation.

6+ years of experience with Java Spark. Strong understanding of distributed computing, big data principles, and batch/stream processing. Proficiency in working with AWS services such as S3, EMR, Glue, Lambda, and Athena. Experience with Data Lake architectures and handling large volumes of structured and unstructured data. Familiarity with various data formats. Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Design, develop, and optimize large-scale data processing pipelines using Java Spark Build scalable solutions to manage data ingestion, transformation, and storage in AWS-based Data Lake environments. Collaborate with data architects and analysts to implement data models and workflows aligned with business requirements. Ensure performance tuning, fault tolerance, and reliability of distributed data processing systems.

6+ years of experience with Java Spark. Strong understanding of distributed computing, big data principles, and batch/stream processing. Proficiency in working with AWS services such as S3, EMR, Glue, Lambda, and Athena. Experience with Data Lake architectures and handling large volumes of structured and unstructured data. Familiarity with various data formats. Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Design, develop, and optimize large-scale data processing pipelines using Java Spark Build scalable solutions to manage data ingestion, transformation, and storage in AWS-based Data Lake environments. Collaborate with data architects and analysts to implement data models and workflows aligned with business requirements. Ensure performance tuning, fault tolerance, and reliability of distributed data processing systems.

10+ years of experience with Java Spark. Strong understanding of distributed computing, big data principles, and batch/stream processing. Proficiency in working with AWS services such as S3, EMR, Glue, Lambda, and Athena. Experience with Data Lake architectures and handling large volumes of structured and unstructured data. Familiarity with various data formats. Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Design, develop, and optimize large-scale data processing pipelines using Java Spark Build scalable solutions to manage data ingestion, transformation, and storage in AWS-based Data Lake environments. Collaborate with data architects and analysts to implement data models and workflows aligned with business requirements.

Educational Bachelor of Engineering Service Line Strategic Technology Group Responsibilities Power Programmer is an important initiative within Global Delivery to develop a team of Full Stack Developers who will be working on complex engineering projects, platforms and marketplaces for our clients using emerging technologies., They will be ahead of the technology curve and will be constantly enabled and trained to be Polyglots., They are Go-Getters with a drive to solve end customer challenges and will spend most of their time in designing and coding, End to End contribution to technology oriented development projects., Providing solutions with minimum system requirements and in Agile Mode., Collaborate with Power Programmers., Open Source community and Tech User group., Custom Development of new Platforms & Solutions ,Opportunities., Work on Large Scale Digital Platforms and marketplaces., Work on Complex Engineering Projects using cloud native architecture ., Work with innovative Fortune 500 companies in cutting edge technologies., Co create and develop New Products and Platforms for our clients., Contribute to Open Source and continuously upskill in latest technology areas., Incubating tech user group Technical and Professional : Bigdata Spark, scala, hive, kafka Preferred Skills: Technology-Big Data-Hbase Technology-Big Data-Sqoop Technology-Functional Programming-Scala Technology-Big Data - Data Processing-Spark-SparkSQL

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

4+ years of experience as a Data Engineer or similar role. Proficiency in Python, PySpark, and advanced SQL. Hands-on experience with big data tools and frameworks (e.g., Spark, Hive). Experience with cloud data platforms like AWS, Azure, or GCP is a plus. Solid understanding of data modeling, warehousing, and ETL processes. Strong problem-solving and analytical skills. Good communication and teamwork abilities.Design, build, and maintain data pipelines that collect, process, and store data from various sources. Integrate data from multiple heterogeneous sources such as databases (SQL/NoSQL), APIs, cloud storage, and flat files. Optimize data processing tasks to improve execution efficiency, reduce costs, and minimize processing times, especially when working with large-scale datasets in Spark. Design and implement data warehousing solutions that centralize data from multiple sources for analysis.

Experience in SQL and understanding of ETL best practices Should have good hands on in ETL/Big Data development Extensive hands on experience in Scala Should have experience in Spark/Yarn, troubleshooting Spark, Linux, Python Setting up a Hadoop cluster, Backup, recovery, and maintenance.

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Apache Spark Good to have skills : AWS GlueMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and optimize data workflows, ensuring that the data infrastructure supports the organization's analytical needs effectively. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge in data engineering.- Continuously evaluate and improve data processing workflows to enhance efficiency and performance. Professional & Technical Skills: - Must To Have Skills: Proficiency in Apache Spark.- Good To Have Skills: Experience with AWS Glue.- Strong understanding of data pipeline architecture and design.- Experience with ETL processes and data integration techniques.- Familiarity with data quality frameworks and best practices. Additional Information:- The candidate should have minimum 5 years of experience in Apache Spark.- This position is based at our Hyderabad office.- A 15 years full time education is required. Qualification 15 years full time education

Immediate Openings on Big data engineer/Developer _ Pan India_Contract Experience 5+ Years Skills Big data engineer/Developer Location Pan India Notice Period Immediate . Employment Type Contract Working Mode Hybrid Big data engineer/Developer Spark-Scala HQL, Hive Control-m Jinkins Git Technical analysis and up to some extent business analysis (knowledge about banking products, credit cards and its transactions)

Education Bachelors degree in Computer Science, Engineering, or a related field. A Masters degree is preferred. Experience Minimum of 4+ years of experience in data engineering or a similar role. Strong programming skills in Python programming and advance SQL. strong experience in NumPy, Pnadas, Data frames Strong analytical and problem-solving skills. Excellent communication and collaboration abilities.

1. Understanding the NBA requirements. 2. Provide Subject matter expertise in relation to Pega CDH from technology perspective. 3. Participate actively in the creation and review of the Conceptual Design, Detailed Design, and estimations. 4. Implementing the NBAs as per agreed requirement/solution 5. Supporting the end-to-end testing and provide fixes with quick TAT. 6. Deployment knowledge to manage the implementation activities. 7. Experience in Pega CDH v8.8 multi app or 24.1 and retail banking domain is preferred. 8. Good communication skills Bangalore/Chennai/Hyderabad/Kolkata _ #Notice Period Immediate #Employment TypeContract

Looking for senior pyspark developer with 6+ years of hands on experienceBuild and manage large scale data solutions using tools like Pyspark, Hadoop, Hive, Python & SQLCreate workflows to process data using IBM TWSAble to use pyspark to create different reports and handle large datasetsUse HQL/SQL/Hive for ad-hoc query data and generate reports, and store data in HDFS Able to deploy code using Bitbucket, Pycharm and Teamcity.Can manage folks, able to communicate with several teams and can explain problem/solutions to business team in non-tech manner -Primary Skill Pyspark-Hadoop-Spark - One to Three Years,Developer / Software Engineer

Design and implement data architecture and models for Big Data solutions using MapR and Hadoop ecosystems. You will optimize data storage, ensure data scalability, and manage complex data workflows. Expertise in Big Data, Hadoop, and MapR architecture is required for this position.

Design and implement Big Data solutions using Hadoop and MapR ecosystem. You will work with data processing frameworks like Hive, Pig, and MapReduce to manage and analyze large data sets. Expertise in Hadoop and MapR is required.

Design, implement, and optimize Big Data solutions using Hadoop technologies. You will work on data ingestion, processing, and storage, ensuring efficient data pipelines. Strong expertise in Hadoop, HDFS, and MapReduce is essential for this role.

Develops data processing solutions using Scala and PySpark.

Design and implement big data solutions using Hadoop ecosystem tools like MapR. Develop data models, optimize data storage, and ensure seamless integration of big data technologies into enterprise systems.

Immediate job opening for # Python+SQL_C2H_Pan India. #Skill:Python+SQL #Job description: Strong programming skills in Python programming and advance SQL. strong experience in NumPy, Pandas, Data frames Strong analytical and problem-solving skills. Excellent communication and collaboration abilities.

Experience in Cloud platform, e.g., AWS, GCP, Azure, etc. Experience in distributed technology tools, viz. SQL, Spark, Python, PySpark, Scala Performance Turing Optimize SQL, PySpark for performance Airflow workflow scheduling tool for creating data pipelines GitHub source control tool & experience with creating/ configuring Jenkins pipeline Experience in EMR/ EC2, Databricks etc. DWH tools incl. SQL database, Presto, and Snowflake Streaming, Serverless Architecture

Immediate Job Openings on #Big Data Engineer _ Pan India_ Contract Experience: 6 +Years Skill:Big Data Engineer Location: Pan India Notice Period:Immediate. Employment Type: Contract Pyspark Azure Data Bricks Experience on workflows Unity catalog Managed / external data with delta tables.

Company: Marsh McLennan Agency Description: Marsh McLennan is seeking candidates for the following position based in the Pune office. Senior Engineer/Principal Engineer What can you expect We are seeking a skilled Data Engineer with 3 to 5 years of hands-on experience in building and optimizing data pipelines and architectures. The ideal candidate will have expertise in Spark, AWS Glue, AWS S3, Python, complex SQL, and AWS EMR. What is in it for you Holidays (As Per the location) Medical & Insurance benefits (As Per the location) Shared Transport (Provided the address falls in service zone) Hybrid way of working Diversify your experience and learn new skills Opportunity to work with stakeholders globally to learn and grow We will count on you to: Design and implement scalable data solutions that support our data-driven decision-making processes. What you need to have: SQL and RDBMS knowledge - 5/5. Postgres. Should have extensive hands-on Database systems carrying tables, schema, views, materialized views. AWS Knowledge. Core and Data engineering services. Glue/ Lambda/ EMR/ DMS/ S3 - services in focus. ETL data:dge :- Any ETL tool preferably Informatica. Data warehousing. Big data:- Hadoop - Concepts. Spark - 3/5 Hive - 5/5 Python/ Java. Interpersonal skills:- Excellent communication skills and Team lead capabilities. Understanding of data systems well in big organizations setup. Passion deep diving and working with data and delivering value out of it. What makes you stand out Databricks knowledge. Any Reporting tool experience. Preferred MicroStrategy. Marsh McLennan (NYSEMMC) is the worlds leading professional services firm in the areas ofrisk, strategy and people. The Companys more than 85,000 colleagues advise clients in over 130 countries.With annual revenue of $23 billion, Marsh McLennan helps clients navigate an increasingly dynamic and complex environment through four market-leading businesses.Marshprovides data-driven risk advisory services and insurance solutions to commercial and consumer clients.Guy Carpenter develops advanced risk, reinsurance and capital strategies that help clients grow profitably and pursue emerging opportunities. Mercer delivers advice and technology-driven solutions that help organizations redefine the world of work, reshape retirement and investment outcomes, and unlock health and well being for a changing workforce. Oliver Wyman serves as a critical strategic, economic and brand advisor to private sector and governmental clients. For more information, visit marshmclennan.com , or follow us onLinkedIn andX . Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people regardless of their sex/gender, marital or parental status, ethnic origin, nationality, age, background, disability, sexual orientation, caste, gender identity or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person. Marsh McLennan (NYSEMMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businessesMarsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit marshmclennan.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person.