Vice President Of Technology

2 weeks ago

Gurgaon, Haryana, India Bluepi Full time
About Blue Pi-Blue Pi Consulting partners with organizations to help them achieve higher levels of maturity.
Founded in 2012, has today grown to serve several established organizations across India & Australia.
Self-funded, the organization has its sales offices in Mumbai & Sydney, besides its headquarters in Gurgaon.
For over a decade, Blue Pi has helped organizations transform their businesses by providing data driven business insights.
It specializes in custom data, analytics and AI/ML solutions that help drive business outcomes for organizations.

Blue Pi works with technology partners – Amazon Web Services (AWS), Snowflake, Google Cloud Platform (GCP), & Databricks.


About the role-The VP Technology is a senior leadership role that oversees the technical vision, strategy, and delivery of data and analytics solutions for Blue Pi Consulting's clients.


The VP Technology is responsible for leading a team of architects, engineers, and consultants, as well as collaborating with sales, marketing, and delivery teams to ensure customer satisfaction and business growth.


Within this role you are expected to be a thought leader and an evangelist for Blue Pi Consulting's data and analytics capabilities, both internally and externally.


Key Responsibilities-Define and execute the technical vision, strategy, and roadmap for data and analytics solutions across various domains and industries.

Lead and mentor a team of architects, engineers, and consultants to design, develop, and deliver high-quality data and analytics solutions that meet customer requirements and expectations.

Collaborate with sales, marketing, and delivery teams to provide technical guidance, support, and solutions for pre-sales, proposals, demos, proofs of concept, and project delivery.

Establish and maintain strong relationships with key stakeholders, decision makers, and influencers at client organizations, as well as partners and vendors.

Identify and evaluate new technologies, tools, frameworks, and best practices for data and analytics solutions, and ensure their adoption and implementation across the organization.

Represent and promote Blue Pi Consulting's data and analytics capabilities and thought leadership at industry events, conferences, webinars, blogs, podcasts, and social media.

Qualifications-Bachelor's degree or higher in Computer Science, Engineering, Mathematics, Statistics, or related field.
15+ years of experience in IT services, with at least 10 years of experience in data and analytics domain.

Proven track record of leading and delivering complex data and analytics solutions for large-scale enterprise clients across various domains and industries.

Expertise in data and analytics technologies, such as cloud platforms, data warehouses, data lakes, data pipelines, data integration, data quality, data governance, data visualization, business intelligence, machine learning, artificial intelligence, and big data.

Strong leadership, communication, presentation, and interpersonal skills, with the ability to influence and inspire teams and clients.

Strong business acumen, analytical skills, and problem-solving skills, with the ability to understand customer needs and provide innovative and value-added solutions.

Mandatory skills-Cloud platforms: AWS, Azure, or GCP

Data warehouses:
Snowflake, Redshift, Big Query, or Synapse

Data lakes:
S3, ADLS, or GCS

Data pipelines:
Airflow, Luigi, or Prefect

Data integration:
Talend, Informatica, or Data Stage

Data quality:
Great Expectations, Deequ, or Databricks Delta Lake

Data governance:
Collibra, Alation, or AWS Glue

Data visualization:
Tableau, Power BI, or Qlik

Business intelligence:
Looker, Micro Strategy, or Cognos

Machine learning:
Tensor Flow, Py Torch, or Scikit-learn

Artificial intelligence:
AWS Sage Maker, Azure ML, or GCP AI Platform

Big data:
Hadoop, Spark, or Kafka

Programming languages:
Python, Scala, or Java

Desirable skills-Data engineering: Databricks, AWS EMR, or Azure Databricks

Data science:
Jupyter, RStudio, or Colab

Data Ops:
MLflow, Kubeflow, or DVC

MLOps:
AWS Sagemaker Pipelines, Azure ML Pipelines, or GCP Vertex AI Pipelines

Dev Ops:
Git, Jenkins, or Docker

Agile:
Scrum, Kanban, or SAFe

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