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Enterprise Data Architect
Enterprise Data Architect
Dataeconomy's logo

Enterprise Data Architect

Saikumar Guttikonda's profile picture
Posted by Saikumar Guttikonda
20 - 25 yrs
Best in industry
Hyderabad, Pune
Skills
Enterprise Data Warehouse (EDW)
TOGAF
skill iconAmazon Web Services (AWS)
MDM
Data architecture
Data warehouse architecture
ETL architecture

Enterprise Data Architect - Dataeconomy (25+ Years Experience)


About Dataeconomy:


Dataeconomy is a rapidly growing company at the forefront of Information Technology. We are driven by data and committed to using it to make better decisions, improve our products, and deliver exceptional value to our customers.

Job Summary:


Dataeconomy seeks a seasoned and strategic Enterprise Data Architect to lead the company's data transformation journey. With 25+ years of experience in data architecture and leadership, you will be pivotal in shaping our data infrastructure, governance, and culture. You will leverage your extensive expertise to build a foundation for future growth and innovation, ensuring our data assets are aligned with business objectives and drive measurable value.


Responsibilities:

Strategic Vision and Leadership:

Lead the creation and execution of a long-term data strategy aligned with the company's overall vision and goals.

Champion a data-driven culture across the organization, fostering cross-functional collaboration and data literacy.

Advise senior leadership on strategic data initiatives and their impact on business performance.

Architecture and Modernization:

Evaluate and modernize the existing data architecture, recommending and implementing innovative solutions.

Design and implement a scalable data lake/warehouse architecture for future growth.

Advocate for and adopt cutting-edge data technologies and best practices.

ETL Tool Experience (8+ years):

Extensive experience in designing, developing, and implementing ETL (Extract, Transform, Load) processes using industry-standard tools such as Informatica PowerCenter, IBM DataStage, Microsoft SSIS, or open-source options like Apache Airflow.

Proven ability to build and maintain complex data pipelines that integrate data from diverse sources, transform it into usable formats, and load it into target systems.

Deep understanding of data quality and cleansing techniques to ensure the accuracy and consistency of data across the organization.

Data Governance and Quality:

Establish and enforce a comprehensive data governance framework ensuring data integrity, consistency, and security.

Develop and implement data quality standards and processes for continuous data improvement.

Oversee the implementation of master data management and data lineage initiatives.

Collaboration and Mentorship:

Mentor and guide data teams, including architects, engineers, and analysts, on data architecture principles and best practices.

Foster a collaborative environment where data insights are readily shared and acted upon across the organization.

Build strong relationships with business stakeholders to understand and translate their data needs into actionable solutions.

Qualifications:

Education: master’s degree in computer science, Information Systems, or related field; Ph.D. preferred.

Experience: 25+ years of experience in data architecture and design, with 10+ years in a leadership role.

Technical Skills:

Deep understanding of TOGAF, AWS, MDM, EDW, Hadoop ecosystem (MapReduce, Hive, HBase, Pig, Flume, Scoop), cloud data platforms (Azure Synapse, Google Big Query), modern data pipelines, streaming analytics, data governance frameworks.

Proficiency in programming languages (Java, Python, SQL), scripting languages (Bash, Python), data modelling tools (ER diagramming software), and BI tools.

Extensive expertise in ETL tools (Informatica PowerCenter, IBM DataStage, Microsoft SSIS, Apache Airflow)

Familiarity with emerging data technologies (AI/ML, blockchain), data security and compliance frameworks.

Soft Skills:

Outstanding communication, collaboration, and leadership skills.

Strategic thinking and problem-solving abilities with a focus on delivering impactful solutions.

Strong analytical and critical thinking skills.

Ability to influence and inspire teams to achieve goals.

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Shubham Vishwakarma

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About Dataeconomy

Founded :
2018
Type :
Products & Services
Size :
100-1000
Stage :
Profitable

About

We are a fast-growing Data & Analytics company with a global presence. We are well-differentiated and are known for our thought leadership, out-of-the-box products, cutting-edge solutions accelerators, innovative use cases, and cost-effective service offerings. GENESIS AND MISSION: Our vision and mission are "Enabling businesses to MONETIZE DATA at data speeds." We accomplish this enablement in 3 areas of expertise: • building Strategies to Monetize data for disruptive business models • Innovate in our Garage, a plug-and-play ecosystem that provides a combination of frameworks, infrastructure, tools, and resources that creates and enables competitive business advantage through Ideation, Prototyping &Hypothesize Feasibility Analysis, and Enterprise Alignment • deliver solutions at fractional costs by leveraging our out-of-the-box solutions to Accelerate Outcomes for differentiated customer experience, operational efficiencies, and business growth through data-driven actional insights We believe that the industry is pivotal, with considerable opportunities in reimagining business models and scaling business operations by leveraging next generations technologies and ecosystem players in Big Data, Data Science, Robotics, Blockchain, Cloud, and DevOps. The genesis of DATAECONOMY stems from our understanding that there is an abundance of untapped potential in Technology, People, and the merger of Machines and People for advancement in technology initiatives. After spending more than two decades with large global consulting services companies serving Fortune 500 companies, we founded DATAECONOMY in June 2018 to advance our charter and our mission is to "Commoditize the Niche" by tackling future challenges of scale and complexity through applied innovation.
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