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IoT Architect

Accenture

IoT Architect

Accenture

·

On-site

·

Full-time

·

4d ago

Project Role: IoT Architect

Project Role Description: Design end-to-end IoT platform architecture solutions, including data ingestion, data processing, and analytics across different vendor platforms for highly interconnected device workloads at scale.

Must have skills: Data Architecture Principles

Good to have skills: NA

Minimum 12 year(s) of experience is required

Educational Qualification: 15 years full time education

Summary:

We are seeking a highly skilled and experienced Industrial Data Architect with a proven track record in providing functional and/or technical expertise to plan, analyze, define and support the delivery of future functional and technical capabilities for an application or group of applications. Well versed with OT data quality, Data modelling, data governance, data contextualization, database design, and data warehousing.

Roles & Responsibilities:

  1. Industrial Data Architect will be responsible for developing and overseeing the industrial data architecture strategies to support advanced data analytics, business intelligence, and machine learning initiatives. This role involves collaborating with various teams to design and implement efficient, scalable, and secure data solutions for industrial operations.
  2. Focused on designing, building, and managing the data architecture of industrial systems.
  3. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests.
  4. Own the offerings and assets on key components of data supply chain, data governance, curation, data quality and master data management, data integration, data replication, data virtualization.
  5. Create scalable and secure data structures, integrate with existing systems, and ensure efficient data flow.

Professional & Technical Skills:

1.Must have Skills: Domain knowledge in areas of Manufacturing IT OT in one or more of the following verticals Automotive, Discrete Manufacturing, Consumer Packaged Goods, Life Science.
2. Data Modeling and Architecture: Proficiency in data modeling techniques (conceptual, logical, and physical models).
3. Knowledge of database design principles and normalization.
4. Experience with data architecture frameworks and methodologies (e.g., TOGAF).
5. Database Technologies: Relational Databases: Expertise in SQL databases such as MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.
6. NoSQL Databases: Experience with at least one of the NoSQL databases like MongoDB, Cassandra, and Couchbase for handling unstructured data.
7. Graph Databases: Proficiency with at least one of the graph databases such as Neo4j, Amazon Neptune, or ArangoDB. Understanding of graph data models, including property graphs and RDF (Resource Description Framework).
8. Query Languages: Experience with at least one of the query languages like Cypher (Neo4j), SPARQL (RDF), or Gremlin (Apache Tinker Pop). Familiarity with ontologies, RDF Schema, and OWL (Web Ontology Language). Exposure to semantic web technologies and standards.
9. Data Integration and ETL (Extract, Transform, Load): Proficiency in ETL tools and processes (e.g., Talend, Informatica, Apache Ni Fi).
10. Experience with data integration tools and techniques to consolidate data from various sources.
11. IoT and Industrial Data Systems: Familiarity with Industrial Internet of Things (IIoT) platforms and protocols (e.g., MQTT, OPC UA).
12. Experience with IoT data platforms like AWS IoT, Azure IoT Hub, and Google Cloud IoT Core.
13. Experience working with one or more of Streaming data platforms like Apache Kafka, Amazon Kinesis, Apache Flink
14. Ability to design and implement real-time data pipelines. Familiarity with processing frameworks such as Apache Storm, Spark Streaming, or Google Cloud Dataflow.
15. Understanding event-driven design patterns and practices. Experience with message brokers like RabbitMQ or ActiveMQ.
16. Exposure to the edge computing platforms like AWS Io

T Greengrass or Azure IoT Edge:

  1. AI/ML, GenAI: Experience working on data readiness for feeding into AI/ML/GenAI applications
  2. Exposure to machine learning frameworks such as Tensor Flow, Py Torch, or Keras.
  3. Cloud Platforms: Experience with cloud data services from at least one of the providers like AWS (Amazon Redshift, AWS Glue), Microsoft Azure (Azure SQL Database, Azure Data Factory), and Google Cloud Platform (Big Query, Dataflow).
  4. Data Warehousing and BI Tools: Expertise in data warehousing solutions (e.g., Snowflake, Amazon Redshift, Google Big Query).
  5. Proficiency with Business Intelligence (BI) tools such as Tableau, Power BI, and Qlik View.
  6. Data Governance and Security: Understanding data governance principles, data quality management, and metadata management.
  7. Knowledge of data security best practices, compliance standards (e.g., GDPR, HIPAA), and data masking techniques.
  8. Big Data Technologies: Experience with big data platforms and tools such as Hadoop, Spark, and Apache Kafka.
  9. Understanding distributed computing and data processing frameworks.

Additional Info:

  1. A minimum of 15-18 years of progressive information technology experience is required.
  2. This position is based at Bengaluru location.
  3. A 15 years full-time education is required.
  4. AWS Certified Data Engineer Associate / Microsoft Certified: Azure Data Engineer Associate / Google Cloud Certified Professional Data Engineer certification is mandatory

15 years full time education

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
Visit us at www.accenture.com

Equal Employment Opportunity Statement

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.

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About Accenture

Accenture

Accenture

Public

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10,001+

Employees

Dublin

Headquarters

Reviews

4.0

10 reviews

Work Life Balance

3.5

Compensation

4.0

Culture

4.2

Career

4.1

Management

4.0

75%

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Pros

Great learning and development opportunities

Supportive and collaborative work environment

Good career growth and networking opportunities

Cons

Need to be proactive in finding projects

Long hours during busy periods

Very competitive environment for advancement

Salary Ranges

33 data points

L2

L3

L4

L5

L6

L2 · Business Analyst L2

0 reports

$63,830

total / year

Base

$25,532

Stock

$31,915

Bonus

$6,383

$44,681

$82,979

Interview Experience

6 interviews

Difficulty

2.7

/ 5

Duration

14-28 weeks

Offer Rate

17%

Experience

Positive 0%

Neutral 50%

Negative 50%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical/Task-Based Interview

4

Final Interview

5

Offer

Common Questions

Technical Knowledge

Behavioral/STAR

Past Experience

Case Study