Senior Data Engineer

DigiKey Global Capability Center; Bengaluru; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A prominent tech organization in Bengaluru seeks a Sr Data Engineer to develop and optimize their cloud data platform. Responsibilities include designing scalable data pipelines, collaborating with cross-functional teams, and mentoring junior engineers. Candidates should have 6+ years of experience in data engineering, expert knowledge in SQL and Python, and familiarity with tools like Snowflake and dbt-core. This role offers a full-time employment opportunity at a mid-senior level in a fast-paced environment.

Qualifications

• 6+ years of experience in data engineering or a related field.
• Expert-level proficiency in SQL and Python for data transformation.
• Experience with dbt-core for data modeling.
• Strong hands-on experience in cloud platforms like Microsoft Azure.

Responsibilities

• Design and implement scalable data pipelines using dbt-core, Python, and SQL.
• Design and optimize data models in Snowflake for efficient storage.
• Collaborate with cross-functional teams to understand data needs.
• Mentor junior data engineers and foster technical excellence.

Skills

SQL

Python

dbt-core

Data warehousing architecture

Data governance

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

Microsoft Azure

Git

Microsoft VSCode

Azure DevOps

Job description

Lead Talent Acquisition at DigiKey India | Ex ANSR | Building High-Impact Global Capability Centers (GCCs) | Talent Acquisition

About the Role

We are seeking a highly experienced and strategic Sr Data Engineer for the development and optimization of our modern cloud data platform infrastructure. This role is ideal for someone who thrives in a fast‑paced environment, is passionate about data architecture, and has a deep understanding of data transformation, modeling, and orchestration using modern tools like dbt-core, Snowflake, and Python.

Key Responsibilities

• Design and implement scalable data pipelines using dbt-core, Python, and SQL to support analytics, reporting, and data science initiatives.
• Design and optimize data models in Snowflake to support efficient querying and storage.
• Development and maintenance of our data warehouse, ensuring data quality, governance, and performance.
• Collaborate with cross‑functional teams including data analysts, data architects, data scientists, and business stakeholders to understand data needs and deliver robust solutions.
• Establish and enforce best practices for version control (Git), CI/CD pipelines, and data pipeline monitoring.
• Mentor and guide junior data engineers, fostering a culture of technical excellence and continuous improvement.
• Evaluate and recommend new tools and technologies to enhance the data platform.
• Provide ongoing support for the existing ELT/ETL processes and procedures.
• Identify tools and technologies to be used in the project as well as reusable objects that could be customized for the project Coding.

Required Qualifications

• Bachelor's degree in Computer Science or related field (16 years of formal education related to engineering).
• 6+ years of experience in data engineering or a related field.
• Expert‑level proficiency in SQL and Python for data transformation and automation.
• Experience with dbt-core for data modeling and transformation.
• Strong hands‑on experience in cloud platforms (Microsoft Azure) and cloud data platforms (Snowflake).
• Proficiency with Git and collaborative development workflows. Familiarity with Microsoft VSCode or similar IDEs. Knowledge of Azure DevOps or Gitlab development operations and job scheduling tools.
• Solid understanding of modern data warehousing architecture, dimensional modeling, ELT/ETL frameworks and data modeling techniques.
• Excellent communication skills and the ability to translate complex technical concepts to non‑technical stakeholders.
• Proven expertise in designing and implementing batch and streaming data pipelines to support near real‑time and large‑scale data processing needs.

Preferred Qualifications

• Experience working in a cloud‑native environment (AWS, Azure, or GCP).
• Familiarity with data governance, security, and compliance standards.
• Prior experience with Apache Kafka (Confluent).
• Artificial Intelligence (AI) experience is a plus.
• Hands‑on experience with orchestration tools (e.g., Airflow, Prefect) is a plus.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Information Technology

Industries

Appliances, Electrical, and Electronics Manufacturing

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