Overview
On Site
Hybrid
BASED ON EXPERIENCE
Full Time
Contract - W2
Contract - Independent
Skills
Management
Data Flow
Reporting
Predictive Modelling
Machine Learning (ML)
Statistics
Prototyping
Algorithms
Data Quality
Data Acquisition
Analytical Skill
Data Analysis
Collaboration
Access Control
Encryption
Data Masking
Data Visualization
Presentations
Dashboard
Programming Languages
Python
Java
Apache Spark
Process Automation
Messaging
SQL
Amazon RDS
Remote Desktop Services
Amazon Redshift
Amazon DynamoDB
MongoDB
Data Processing
Scalability
Data Engineering
Graph Databases
Resource Description Framework
Database
Insurance
Mortgage
Banking
Amazon Kinesis
Apache Kafka
Docker
Kubernetes
Continuous Integration
Continuous Delivery
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud
Google Cloud Platform
Natural Language Processing
Application Development
Software Modernization
Process Outsourcing
IT Service Management
Job Details
Job description:-
Location: Dallas, TX & NY/NJ (3 Days Onsite in a week)
Full time and W2 preferred
Job Description:
Looking for a data professional with expertise in data engineering and programming to build systems that collect, manage, and convert raw data into usable information for business requirements. As a Data Engineer, you'll play a crucial role in ensuring data reliability, quality, and efficiency within the organization.
Responsibilities :
Analyze and organize raw data: Work with various data sources, document parsing, extracting relevant information and structuring it for further processing.
Build data systems and pipelines: Construct robust data pipelines that facilitate data flow from source to Target.
Evaluate business needs and objectives: Understand the company's requirements and align data systems accordingly.
Interpret trends and patterns: Use your analytical skills to identify data patterns.
Conduct complex data analysis and report on results: Dive deep into data to extract meaningful information.
Prepare data for prescriptive and predictive modeling: Ensure data is ready for machine learning and statistical analysis.
Build algorithms and prototypes: Develop and test data processing algorithms.
Combine raw information from different sources: Integrate data from various systems.
Explore ways to enhance data quality and reliability: Continuously improve data processes.
Identify opportunities for data acquisition: Stay informed about new data sources.
Develop analytical tools and programs: Create tools to facilitate data analysis.
Collaborate with data scientists and architects: Work closely with other data professionals to achieve common goals.
Implement data access controls, data encryption, and data masking techniques
Familiarity with data visualization tools and techniques for presenting data
Create and maintain dashboards and reports for stakeholders.
Mandatory Skills :
Previous experience as a data engineer or in a similar role with at least 6+ years of relevant work experience.
Good knowledge of programming languages (e.g., Python, Java, Spark, etc).
Design, develop, and maintain data pipelines.
Exposure to process automation.
Experience working with REST APIs and services, messaging and event technologies.
Experience working with large and complex data sets.
Hands-on experience with SQL/No-SQL database (RDS, Redshift, DynamoDB, synapse, big query, mongo, etc.)
Batch/stream data processing experience
Monitor, troubleshoot, and optimize the performance of data infrastructure to ensure scalability, reliability, and cost efficiency.
Stay up to date with cloud services and best practices in data engineering to continuously improve our data ecosystem.
Good exposure on at least two public cloud platforms (Azure/AWS/Google Cloud Platform)
Experience with Graph database (e.g. Neptune, RDF4j, etc.)
Experience with Vector database (e.g. Pinecone, FAISS, etc.)
Good-to-Have Skills :
- knowledge or work experience in insurance, mortgage, banking domains.
- Proficiency in building stream processing systems using kinesis, Kafka, etc.
- Familiarity with Docker, Kubernetes, CI/CD and cloud services (AWS, Azure, Google Cloud Platform).
- Technical expertise with segmentation techniques.
- NLP knowledge
Role: Data engineer
Location: Dallas, TX & NY/NJ (3 Days Onsite in a week)
Full time and W2 preferred
Job Description:
Looking for a data professional with expertise in data engineering and programming to build systems that collect, manage, and convert raw data into usable information for business requirements. As a Data Engineer, you'll play a crucial role in ensuring data reliability, quality, and efficiency within the organization.
Responsibilities :
Analyze and organize raw data: Work with various data sources, document parsing, extracting relevant information and structuring it for further processing.
Build data systems and pipelines: Construct robust data pipelines that facilitate data flow from source to Target.
Evaluate business needs and objectives: Understand the company's requirements and align data systems accordingly.
Interpret trends and patterns: Use your analytical skills to identify data patterns.
Conduct complex data analysis and report on results: Dive deep into data to extract meaningful information.
Prepare data for prescriptive and predictive modeling: Ensure data is ready for machine learning and statistical analysis.
Build algorithms and prototypes: Develop and test data processing algorithms.
Combine raw information from different sources: Integrate data from various systems.
Explore ways to enhance data quality and reliability: Continuously improve data processes.
Identify opportunities for data acquisition: Stay informed about new data sources.
Develop analytical tools and programs: Create tools to facilitate data analysis.
Collaborate with data scientists and architects: Work closely with other data professionals to achieve common goals.
Implement data access controls, data encryption, and data masking techniques
Familiarity with data visualization tools and techniques for presenting data
Create and maintain dashboards and reports for stakeholders.
Mandatory Skills :
Previous experience as a data engineer or in a similar role with at least 6+ years of relevant work experience.
Good knowledge of programming languages (e.g., Python, Java, Spark, etc).
Design, develop, and maintain data pipelines.
Exposure to process automation.
Experience working with REST APIs and services, messaging and event technologies.
Experience working with large and complex data sets.
Hands-on experience with SQL/No-SQL database (RDS, Redshift, DynamoDB, synapse, big query, mongo, etc.)
Batch/stream data processing experience
Monitor, troubleshoot, and optimize the performance of data infrastructure to ensure scalability, reliability, and cost efficiency.
Stay up to date with cloud services and best practices in data engineering to continuously improve our data ecosystem.
Good exposure on at least two public cloud platforms (Azure/AWS/Google Cloud Platform)
Experience with Graph database (e.g. Neptune, RDF4j, etc.)
Experience with Vector database (e.g. Pinecone, FAISS, etc.)
Good-to-Have Skills :
- knowledge or work experience in insurance, mortgage, banking domains.
- Proficiency in building stream processing systems using kinesis, Kafka, etc.
- Familiarity with Docker, Kubernetes, CI/CD and cloud services (AWS, Azure, Google Cloud Platform).
- Technical expertise with segmentation techniques.
- NLP knowledge
Additional Job Details:
About Tanisha Systems, Inc.
Tanisha Systems, founded in 2002 in Massachusetts-*, is a leading provider of Custom Application Development and end-to-end IT Services to clients globally. We use a client-centric engagement model that combines local on-site and off-site resources with the cost, global expertise and quality advantages of off-shore operations. We deliver Custom Application Development, Application Modernization, Business Process Outsourcing and Professional IT Services from office locations in * and *.
Tanisha Systems services clients in Government, Banking & Financial Markets, Insurance, Healthcare, Retail & Consumer Goods, Energy & Utilities, Life Sciences, Telecom, Manufacturing and Transportation Industries around the globe. Our engagement model provides a flexible operational environment that empowers our clients with the right levels of control.
Want to read more about Tanisha Systems? Visit us at
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