Job Description
Job Title:  Lead Data Analyst L1
City:  Bengaluru, Chennai
State/Province:  Karnataka, Tamil Nadu
Posting Start Date:  6/2/26

Job Title: GCP Data Architect - Data Pipelines and DataOps

Location: Offshore

 

Job Responsibilities:

  1. Data Architecture and Design:
    • Lead the design and development of scalable and efficient data architectures on GCP, with a focus on data pipelines and DataOps principles.
    • Collaborate with cross-functional teams to understand business requirements and translate them into comprehensive data solutions.
    • Experience in Data Products principles and designing Data API’s
    • Data Ingestion considering System of Records, Systems of Engagement and Systems of Insight
  2. Data Pipelines Expertise:
    • Design, implement, and optimize end-to-end data pipelines, ensuring seamless integration with various data sources and destinations.
    • Implement data streaming and batch processing solutions to support real-time and batch analytics.
  3. DataOps Implementation:
    • Establish and maintain robust DataOps processes to streamline the development, deployment, and monitoring of data pipelines.
    • Implement version control, automated testing, and continuous integration practices for data pipelines.
  4. GCP Data Services Mastery:
    • Possess advanced knowledge and hands-on experience with GCP data services, including BigQuery, Dataflow, Dataprep, Dataproc, and other relevant tools.
    • Stay updated on the latest GCP data services offerings and integrate new technologies into data pipeline architectures.
  5. Data Governance and Security:
    • Implement and enforce data governance policies within the context of DataOps, ensuring data integrity, security, and compliance.
    • Collaborate with security and compliance teams to address any data security concerns in data pipeline processes.
  6. Collaboration and Leadership:
    • Collaborate with data engineers, data scientists, and business stakeholders to understand their requirements and align data architectures with organizational goals.
    • Provide technical leadership and mentorship to junior team members.
  7. Documentation and Best Practices:
    • Maintain comprehensive documentation for data architectures, data pipeline processes, and configurations.
    • Define and promote best practices for data pipeline development, deployment, and monitoring within the organization.
    • Documenting Conceptual, Logical Data Models, data principles, data dictionaries, schema definition and Data API specifications
    • Documenting UML Entity relationship diagrams with entity description, enumerations, payload structure and error response structures.

 

 

Qualifications:

  • Bachelor’s degree in computer science, Information Technology, or a related field.
  • Minimum of 10 years of hands-on experience with GCP data services, data engineering, and a focus on data pipelines and DataOps.
  • Proven experience in designing and implementing complex data architectures with a strong emphasis on data pipelines.
  • Strong proficiency in SQL, Python, or other relevant programming languages.
  • Excellent understanding of data modelling, ETL processes, and data warehousing.
  • Experience with version control systems and CI/CD practices for data pipelines.
  • Strong problem-solving and troubleshooting skills.
  • Ability to communicate complex technical concepts to non-technical stakeholders effectively.
  • Google Cloud Professional Data Engineer or Data Architect certification.
  • Google Products on data like Big Query, Cloud Spanner, Cloud SQL

 

Preferred Qualifications:

  • Experience with machine learning and AI technologies on the GCP platform.
  • Familiarity with advanced analytics, data lakes, and streaming data architectures.
  • Previous experience in financial services is a plus.

 

If you are a result driven GCP Data Architect with a focus on data pipelines and DataOps practices, we invite you to apply for this exciting opportunity.

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Job Description: 

Job Description

Role Purpose

The purpose of this role is to interpret data and turn into information (reports, dashboards, interactive visualizations etc) which can offer ways to improve a business, thus affecting business decisions

͏

Dos

1. Managing the technical scope of the project in line with the requirements at all stages

a. Gather information from various sources (data warehouses, database, data integration and modelling) and interpret patterns and trends

b. Develop record management process and policies

c. Build and maintain relationships at all levels within the client base and understand their requirements.

d. Providing sales data, proposals, data insights and account reviews to the client base

e. Identify areas to increase efficiency and automation of processes

f. Set up and maintain automated data processes

g. Identify, evaluate and implement external services and tools to support data validation and cleansing.

h. Produce and track key performance indicators

 

2. Analyze the data sets and provide adequate information

a. Liaise with internal and external clients to fully understand data content

b. Design and carry out surveys and analyze survey data as per the customer requirement

c. Analyze and interpret complex data sets relating to customer’s business and prepare reports for internal and external audiences using business analytics reporting tools

d. Create data dashboards, graphs and visualization to showcase business performance and also provide sector and competitor benchmarking

e. Mine and analyze large datasets, draw valid inferences and present them successfully to management using a reporting tool

f. Develop predictive models and share insights with the clients as per their requirement

͏

Deilver 

No. Performance Parameter Measure
1. Analyses data sets and provide relevant information to the client No. Of automation done, On-Time Delivery, CSAT score, Zero customer escalation, data accuracy

 

͏

͏

Job Title: GCP Data Architect - Data Pipelines and DataOps

Location: Offshore

 

Job Responsibilities:

  1. Data Architecture and Design:
    • Lead the design and development of scalable and efficient data architectures on GCP, with a focus on data pipelines and DataOps principles.
    • Collaborate with cross-functional teams to understand business requirements and translate them into comprehensive data solutions.
    • Experience in Data Products principles and designing Data API’s
    • Data Ingestion considering System of Records, Systems of Engagement and Systems of Insight
  2. Data Pipelines Expertise:
    • Design, implement, and optimize end-to-end data pipelines, ensuring seamless integration with various data sources and destinations.
    • Implement data streaming and batch processing solutions to support real-time and batch analytics.
  3. DataOps Implementation:
    • Establish and maintain robust DataOps processes to streamline the development, deployment, and monitoring of data pipelines.
    • Implement version control, automated testing, and continuous integration practices for data pipelines.
  4. GCP Data Services Mastery:
    • Possess advanced knowledge and hands-on experience with GCP data services, including BigQuery, Dataflow, Dataprep, Dataproc, and other relevant tools.
    • Stay updated on the latest GCP data services offerings and integrate new technologies into data pipeline architectures.
  5. Data Governance and Security:
    • Implement and enforce data governance policies within the context of DataOps, ensuring data integrity, security, and compliance.
    • Collaborate with security and compliance teams to address any data security concerns in data pipeline processes.
  6. Collaboration and Leadership:
    • Collaborate with data engineers, data scientists, and business stakeholders to understand their requirements and align data architectures with organizational goals.
    • Provide technical leadership and mentorship to junior team members.
  7. Documentation and Best Practices:
    • Maintain comprehensive documentation for data architectures, data pipeline processes, and configurations.
    • Define and promote best practices for data pipeline development, deployment, and monitoring within the organization.
    • Documenting Conceptual, Logical Data Models, data principles, data dictionaries, schema definition and Data API specifications
    • Documenting UML Entity relationship diagrams with entity description, enumerations, payload structure and error response structures.

 

 

Qualifications:

  • Bachelor’s degree in computer science, Information Technology, or a related field.
  • Minimum of 10 years of hands-on experience with GCP data services, data engineering, and a focus on data pipelines and DataOps.
  • Proven experience in designing and implementing complex data architectures with a strong emphasis on data pipelines.
  • Strong proficiency in SQL, Python, or other relevant programming languages.
  • Excellent understanding of data modelling, ETL processes, and data warehousing.
  • Experience with version control systems and CI/CD practices for data pipelines.
  • Strong problem-solving and troubleshooting skills.
  • Ability to communicate complex technical concepts to non-technical stakeholders effectively.
  • Google Cloud Professional Data Engineer or Data Architect certification.
  • Google Products on data like Big Query, Cloud Spanner, Cloud SQL

 

Preferred Qualifications:

  • Experience with machine learning and AI technologies on the GCP platform.
  • Familiarity with advanced analytics, data lakes, and streaming data architectures.
  • Previous experience in financial services is a plus.

 

If you are a result driven GCP Data Architect with a focus on data pipelines and DataOps practices, we invite you to apply for this exciting opportunity.

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