198 Cloudera Jobs - Page 4

Role & responsibilities Bigdata, Hadoop, Hive, SQL, Cloudera, Impala, Python, Pyspark Fundamentals of: Big data Cloudera Platform Unix Python Expertise in: SQL/HIVE Pyspark Nice to have: Django/Flask frameworks

Job Description Skills and Requirements: Resource must have 2+ years of IT Industry experience. Resource must have worked in AEMR, PMTX datasets The Resource must have strong background in data analysis, visualization and be proficient in using SharePoint, Python, Hive tables and Cloudera platform Should be able to Create Tableau Extracts and schedule it based on the requirement. Perform Data analysis to Identify trends and patterns in data extracts that supports business decision making. Should possess Strong SQL skills for data querying and manipulation. Ability to work independently and as part of a team.

Location Mumbai Role Overview : As a Big Data Engineer, you'll design and build robust data pipelines on Cloudera using Spark (Scala/PySpark) for ingestion, transformation, and processing of high-volume data from banking systems. Key Responsibilities : Build scalable batch and real-time ETL pipelines using Spark and Hive Integrate structured and unstructured data sources Perform performance tuning and code optimization Support orchestration and job scheduling (NiFi, Airflow) Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Skills Required : Proficiency in PySpark/Scala with Hive/Impala Experience with data partitioning, bucketing, and optimization Familiarity with Kafka, Iceberg, NiFi is a must Knowledge of banking or financial datasets is a plus

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

Skills and Requirements: Resource must have 2+ years of IT Industry experience. Resource must have worked in AEMR, PMTX datasets The Resource must have strong background in data analysis, visualization and be proficient in using SharePoint, Python, Hive tables and Cloudera platform Should be able to Create Tableau Extracts and schedule it based on the requirement. Perform Data analysis to Identify trends and patterns in data extracts that supports business decision making. Should possess Strong SQL skills for data querying and manipulation. Ability to work independently and as part of a team.

Role Purpose The purpose of this role is to design, develop and troubleshoot solutions/ designs/ models/ simulations on various softwares as per clients/ project requirements Do 1. Design and Develop solutions as per clients specifications Work on different softwares like CAD, CAE to develop appropriate models as per the project plan/ customer requirements Test the protype and designs produced on the softwares and check all the boundary conditions (impact analysis, stress analysis etc) Produce specifications and determine operational feasibility by integrating software components into a fully functional software system Create a prototype as per the engineering drawings & outline CAD model is prepared Perform failure effect mode analysis (FMEA) for any new requirements received from the client Provide optimized solutions to the client by running simulations in virtual environment Ensure software is updated with latest features to make it cost effective for the client Enhance applications/ solutions by identifying opportunities for improvement, making recommendations and designing and implementing systems Follow industry standard operating procedures for various processes and systems as per the client requirement while modeling a solution on the software 2. Provide customer support and problem solving from time to time Perform defect fixing raised by the client or software integration team while solving the tickets raised Develop software verification plans and quality assurance procedures for the customer Troubleshoot, debug and upgrade existing systems on time & with minimum latency and maximum efficiency Deploy programs and evaluate user feedback for adequate resolution with customer satisfaction Comply with project plans and industry standards 3. Ensure reporting & documentation for the client Ensure weekly, monthly status reports for the clients as per requirements Maintain documents and create a repository of all design changes, recommendations etc Maintain time-sheets for the clients Providing written knowledge transfer/ history of the project Deliver No. Performance Parameter Measure 1. Design and develop solutions Adherence to project plan/ schedule, 100% error free on boarding & implementation, throughput % 2. Quality & CSAT On-Time Delivery, minimum corrections, first time right, no major defects post production, 100% compliance of bi-directional traceability matrix, completion of assigned certifications for skill upgradation 3. MIS & Reporting 100% on time MIS & report generation Mandatory Skills: StreamSets. Experience5-8 Years.

Role Purpose The purpose of the role is to support process delivery by ensuring daily performance of the Production Specialists, resolve technical escalations and develop technical capability within the Production Specialists. Do Oversee and support process by reviewing daily transactions on performance parameters Review performance dashboard and the scores for the team Support the team in improving performance parameters by providing technical support and process guidance Record, track, and document all queries received, problem-solving steps taken and total successful and unsuccessful resolutions Ensure standard processes and procedures are followed to resolve all client queries Resolve client queries as per the SLA’s defined in the contract Develop understanding of process/ product for the team members to facilitate better client interaction and troubleshooting Document and analyze call logs to spot most occurring trends to prevent future problems Identify red flags and escalate serious client issues to Team leader in cases of untimely resolution Ensure all product information and disclosures are given to clients before and after the call/email requests Avoids legal challenges by monitoring compliance with service agreements Handle technical escalations through effective diagnosis and troubleshooting of client queries Manage and resolve technical roadblocks/ escalations as per SLA and quality requirements If unable to resolve the issues, timely escalate the issues to TA & SES Provide product support and resolution to clients by performing a question diagnosis while guiding users through step-by-step solutions Troubleshoot all client queries in a user-friendly, courteous and professional manner Offer alternative solutions to clients (where appropriate) with the objective of retaining customers’ and clients’ business Organize ideas and effectively communicate oral messages appropriate to listeners and situations Follow up and make scheduled call backs to customers to record feedback and ensure compliance to contract SLA’s Build people capability to ensure operational excellence and maintain superior customer service levels of the existing account/client Mentor and guide Production Specialists on improving technical knowledge Collate trainings to be conducted as triage to bridge the skill gaps identified through interviews with the Production Specialist Develop and conduct trainings (Triages) within products for production specialist as per target Inform client about the triages being conducted Undertake product trainings to stay current with product features, changes and updates Enroll in product specific and any other trainings per client requirements/recommendations Identify and document most common problems and recommend appropriate resolutions to the team Update job knowledge by participating in self learning opportunities and maintaining personal networks Deliver NoPerformance ParameterMeasure1ProcessNo. of cases resolved per day, compliance to process and quality standards, meeting process level SLAs, Pulse score, Customer feedback, NSAT/ ESAT2Team ManagementProductivity, efficiency, absenteeism3Capability developmentTriages completed, Technical Test performance Mandatory Skills: Hadoop. Experience5-8 Years.

Role Overview : We are looking for aTalend Data Catalog Specialistto drive enterprise data governance initiatives by implementingTalend Data Catalogand integrating it withApache Atlasfor unified metadata management within a Cloudera-based data lakehouse. The role involves establishing metadata lineage, glossary harmonization, and governance policies to enhance trust, discovery, and compliance across the data ecosystem Key Responsibilities: o Set up and configure Talend Data Catalog to ingest and manage metadata from source systems, data lake (HDFS), Iceberg tables, Hive metastore, and external data sources. o Develop and maintain business glossaries , data classifications, and metadata models. o Design and implement bi-directional integration between Talend Data Catalog and Apache Atlas to enable metadata synchronization , lineage capture, and policy alignment across the Cloudera stack. o Map technical metadata from Hive/Impala to business metadata defined in Talend. o Capture end-to-end lineage of data pipelines (e.g., from ingestion in PySpark to consumption in BI tools) using Talend and Atlas. o Provide impact analysis for schema changes, data transformations, and governance rule enforcement. o Support definition and rollout of enterprise data governance policies (e.g., ownership, stewardship, access control). o Enable role-based metadata access , tagging, and data sensitivity classification. o Work with data owners, stewards, and architects to ensure data assets are well-documented, governed, and discoverable. o Provide training to users on leveraging the catalog for search, understanding, and reuse. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 6–12 years in data governance or metadata management, with at least 2–3 years in Talend Data Catalog. Talend Data Catalog, Apache Atlas, Cloudera CDP, Hive/Impala, Spark, HDFS, SQL. Business glossary, metadata enrichment, lineage tracking, stewardship workflows. Hands-on experience in Talend–Atlas integration , either through REST APIs, Kafka hooks, or metadata bridges. Preferred technical and professional experience .

Role Overview : Looking for a Kafka SME to design and support real-time data ingestion pipelines using Kafka within a Cloudera-based Lakehouse architecture. Key Responsibilities : Design Kafka topics, partitions, schema registry Implement producer-consumer apps using Spark Structured Streaming Set up Kafka Connect, monitoring, and alerts Ensure secure, scalable message delivery Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Skills Required : Deep understanding of Kafka internals and ecosystem Integration with Cloudera and NiFi Schema evolution and serialization (Avro, Parquet) Performance tuning and fault-tolerance Preferred technical and professional experience Good communication skill. India market experience is preferred.

Years of Experience : 10-15 Yrs Shifts : 24*7 (Rotational Shift) Mode : Onsite Experience : 10+ yrs of experience in IT, with At least 7+ years of experience with cloud and system administration. At least 5 years of experience with and strong understanding of 'big data' technologies in Hadoop ecosystem - Hive, HDFS, Map/Reduce, Flume, Pig, Cloudera, HBase Sqoop, Spark etc. Job Overview : Smartavya Analytica Private Limited is seeking an experienced Hadoop Administrator to manage and support our Hadoop ecosystem. The ideal candidate will have strong expertise in Hadoop cluster administration, excellent troubleshooting skills, and a proven track record of maintaining and optimizing Hadoop environments. Key Responsibilities: Install, configure, and manage Hadoop clusters, including HDFS, YARN, Hive, HBase, and other ecosystem components. Monitor and manage Hadoop cluster performance, capacity, and security. Perform routine maintenance tasks such as upgrades, patching, and backups. Implement and maintain data ingestion processes using tools like Sqoop, Flume, and Kafka. Ensure high availability and disaster recovery of Hadoop clusters. Collaborate with development teams to understand requirements and provide appropriate Hadoop solutions. Troubleshoot and resolve issues related to the Hadoop ecosystem. Maintain documentation of Hadoop environment configurations, processes, and procedures. Requirement : Experience in Installing, configuring and tuning Hadoop distributions. Hands on experience in Cloudera. Understanding of Hadoop design principals and factors that affect distributed system performance, including hardware and network considerations. Provide Infrastructure Recommendations, Capacity Planning, work load management. Develop utilities to monitor cluster better Ganglia, Nagios etc. Manage large clusters with huge volumes of data Perform Cluster maintenance tasks Create and removal of nodes, cluster monitoring and troubleshooting Manage and review Hadoop log files

Role & responsibilities 4+ years of experience as a Data Engineer or similar role - 3+ of years experience building data solutions at scale using one of the Enterprise Data platforms – Palantir Foundry, Snowflake, Cloudera/Hive, Amazon Redshift - 3+ years of experience with SQL and No-SQL databases (Snowflake or Hive) - 3+ years of hands-on experience with programming using Python, Spark or C# - Experience with DevOps principals and CI/CD - Strong understanding of ETL principles and data integration patterns - Experience with Agile and iterative development processes is a plus - Experience with cloud services such as AWS, Azure etc. and other big data tools like Spark, Kafka, etc. is a plus (not mandatory) - Knowledge of Typescript & Full stack development experience is a plus (not mandatory)

Job Description for the Data Engineering: Location: PAN INDIA Experience between 7 - 14 years in performing the Data Engineering engagement Have experienced in Cloudera, Hadoop and SnowFlake Worked in the Impala and Kudu systems and can write code in Spark, PySpark Experienced in setting up Ooizee workflows Should be very good in SQL Have experience in Performance Tuning

PureSoftware is looking for Data Engineer to join our dynamic team and embark on a rewarding career journey. Liaising with coworkers and clients to elucidate the requirements for each task. Conceptualizing and generating infrastructure that allows big data to be accessed and analyzed. Reformulating existing frameworks to optimize their functioning. Testing such structures to ensure that they are fit for use. Preparing raw data for manipulation by data scientists. Detecting and correcting errors in your work. Ensuring that your work remains backed up and readily accessible to relevant coworkers. Remaining up-to-date with industry standards and technological advancements that will improve the quality of your outputs.

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and Azure Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark and Hive, Hbase or other NoSQL databases on Azure Cloud Data Platform or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / Azure eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala; Minimum 3 years of experience on Cloud Data Platforms on Azure; Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB Good to excellent SQL skills Exposure to streaming solutions and message brokers like Kafka technologies Preferred technical and professional experience Certification in Azure and Data Bricks or Cloudera Spark Certified developers

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"

TCS-FACE TO FACE INTERVIEW 08TH APRIL 2025 IN PUNE CANDIDATES WALKINDRIVE . JOB DESCRIPTION: JD: • True Hands-On Developer in Programming Languages like Java or Scala . • Expertise in Apache Spark . • Database modelling and working with any of the SQL or NoSQL Database is must. • Working knowledge of Scripting languages like shell/python. • Experience of working with Cloudera is Preferred • Orchestration tools like Airflow or Oozie would be a value addition. • Knowledge of Table formats like Delta or Iceberg is plus to have. • Working experience of Version controls like Git, build tools like Maven is recommended. • Having software development experience is good to have along with Data Engineering experience.

Role & responsibilities Design, develop, and maintain data pipelines and architectures that enable fast data transformation and processing. Work with cross-functional teams to identify and prioritize data transformation requirements. Ensure data quality, integrity, and security throughout the data transformation process. Collaborate with data scientists and analysts to develop and optimize data models and algorithms. Optimize data pipeline performance, scalability, and reliability. Develop and maintain technical documentation for data pipelines and architectures Preferred candidate profile Bachelors degree in computer science, Engineering, or a related field. Language Pyspark and Java Data modelling, Data Ingestion , Data Warehouse Should have hands on experience in handling projects on Data Bricks Should have strong Design skills Azure Experience in working on Azure platform with ADF , Databricks , ADLS, Delta Storage Disturbed processing Hadoop , HDFS , Cloudera , Hive Expert on Spark , Pyspark , SQL At least 5+ years of experience in data engineering, software development, or related field. Familiarity with machine learning and data science concepts. Experience with agile development methodologies and version control systems such as Git. Job Locations - PAN India If you're interested, kindly share resume at uma.s@ignitivesearch.com along with the below details, Name: Primary & Secondary mobile number - Primary & Secondary mail ID - Total Experience: Relevant Experience: Current Company: Current Location: Prefer Location: Notice Period: In serving LWD: Current CTC: Expected CTC: PAN No: DOB: Offer (if any):

Azure Data Engineer/Sr. Data Engineer (5+&8+ years) with expertise in Azure(ADF, Databricks, ADLS,Delta Storage), Java, SQL, Spark, Hadoop (HDFS, Cloudera, Hive), data modeling, ingestion, transformation, performance tuning, and technical leadership.

5+ yrs Azure data Engineer PySpark, Java, SQL expert. Data modeling, ingestion, DW. Azure: ADF, Data bricks, ADLS. Hadoop, Hive, Cloudera. Data bricks project experience. Strong design, leadership skills. Agile, Git, ML con. Degree in CS/Engineering.

Qualitest India Private Limited is looking for Data Engineer to join our dynamic team and embark on a rewarding career journey. Liaising with coworkers and clients to elucidate the requirements for each task. Conceptualizing and generating infrastructure that allows big data to be accessed and analyzed. Reformulating existing frameworks to optimize their functioning. Testing such structures to ensure that they are fit for use. Preparing raw data for manipulation by data scientists. Detecting and correcting errors in your work. Ensuring that your work remains backed up and readily accessible to relevant coworkers. Remaining up-to-date with industry standards and technological advancements that will improve the quality of your outputs.

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark, Scala, and Hive, Hbase or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / AWS eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Total 5 - 7+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering skills Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala. Minimum 3 years of experience on Cloud Data Platforms on AWS; Exposure to streaming solutions and message brokers like Kafka technologies. Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB Good to excellent SQL skills Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark, Scala, and Hive, Hbase or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / AWS eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala ; Minimum 3 years of experience on Cloud Data Platforms on AWS; Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB Good to excellent SQL skills Exposure to streaming solutions and message brokers like Kafka technologies Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers.

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and Azure Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark and Hive, Hbase or other NoSQL databases on Azure Cloud Data Platform or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / Azure eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala; Minimum 3 years of experience on Cloud Data Platforms on Azure; Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB Good to excellent SQL skills Exposure to streaming solutions and message brokers like Kafka technologies Preferred technical and professional experience Certification in Azure and Data Bricks or Cloudera Spark Certified developers

As a senior SAP Consultant, you will serve as a client-facing practitioner working collaboratively with clients to deliver high-quality solutions and be a trusted business advisor with deep understanding of SAP Accelerate delivery methodology or equivalent and associated work products. You will work on projects that assist clients in integrating strategy, process, technology, and information to enhance effectiveness, reduce costs, and improve profit and shareholder value. There are opportunities for you to acquire new skills, work across different disciplines, take on new challenges, and develop a comprehensive understanding of various industries. Your primary responsibilities includeStrategic SAP Solution FocusWorking across technical design, development, and implementation of SAP solutions for simplicity, amplification, and maintainability that meet client needs. Comprehensive Solution DeliveryInvolvement in strategy development and solution implementation, leveraging your knowledge of SAP and working with the latest technologies. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Total 5 - 7+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering skills Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala. Minimum 3 years of experience on Cloud Data Platforms on AWS; Exposure to streaming solutions and message brokers like Kafka technologies. Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB Good to excellent SQL skills Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and Azure Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark and Hive, Hbase or other NoSQL databases on Azure Cloud Data Platform or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / Azure eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala; Minimum 3 years of experience on Cloud Data Platforms on Azure; Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB Good to excellent SQL skills Exposure to streaming solutions and message brokers like Kafka technologies Preferred technical and professional experience Certification in Azure and Data Bricks or Cloudera Spark Certified developers