Data technical lead

• 5+ years of experience supporting big data platforms (cloud)
• Exceptional analytical and conceptual thinking skills coupled with strong written and verbal communication skills and ability to solve problems quickly.
• Strong technical skills in data engineering, including proficiency in programming languages and technologies such (Databricks,Azure Data Factory, Python)
• Should be proficient in SQL and Query optimization.
• Technical expertise understanding database design development, data models, and techniques for data mining.
• Expertise in working with various data tools and technologies, such as ETL frameworks, data pipelines, and data warehousing solutions.
• Preferred Cloud computing experience with preference for Microsoft Azure cloud technologies.
• Proven experience in leading a team of data engineers, providing guidance, mentorship, and technical support.
• In-depth knowledge of data management principles and best practices, including data governance, data quality, and data integration.
• Excellent interpersonal skills, with the ability to effectively collaborate with cross-functional teams, stakeholders, and senior management.
• Drive automation efforts across the data analytics team utilizing Infrastructure as Code (IaC) using Terraform, Configuration Management, and Continuous Integration (CI) / Continuous Delivery (CD) tools such as Jenkins.
• Experience designing for data engineering models.
• Able to communicate effectively, both written and orally, with internal and external customers, vendors, and partners.
• Thrives in ambiguous technology situations.
• Ability to solve problems efficiently, think analytically, creatively, and logically.
• Ability to interact effectively with co-workers to accomplish daily tasks and to resolve interpersonal conflicts and miscommunications.
• Must be able to be bonded.
• Ability to maintain a high level of confidentiality.
• Should have experience as a technical lead mentoring data engineer and driving data-oriented projects.
• Should have worked in onshore offshore model managing challenging scenarios.
• Lead data architecture and implementation efforts to structure, integrate, govern, store, describe, model, and maintain data warehouse for optimal accuracy and usage.
• Ability to work with ambiguity and vague requirements and transform them into deliverables.
• Help build define architecture frameworks, best practices & processes. Collaborate on Data warehouse architecture and technical design discussions.
• Should have expertise in data life cycle, data ingestion, transformation, data loading, validation, and performance tuning.

Skill Set Required

Must Have

Good to Have

1

Azure Data Factory

Yes

2

Azure Databricks

Yes

3

Azure Synapse

Yes

4

ADLS

Yes

5

Lakehouse Architecture

Yes

6

Python

Yes

7

SCD Concepts and implementation

Yes

8

SQL, PL/SQL

Yes

9

SSIS

Yes

10

SSAS

Yes

11

TFS

Yes

12

UC4

Yes

13

Power BI

Yes

14

DevOps CI/CD

Yes

15

Cosmos DB

Yes

16

Azure DevOps

Yes

17

Banking Domain

Yes

18

Data Architecture

Yes

19

Certifications in Data Space

Yes