Key Facts

Remote From:

Fixed term

Senior (5-10 years)

English

Hard Skills

Data Engineering SQL (Programming Language) Python (Programming Language) Data Modeling Apache Kafka CI/CD Terraform Apache Iceberg Apache Airflow Airbyte +2 more

Other Skills

•
Leadership
•
Mentorship

Roles & Responsibilities

7–10 years of experience in Data Engineering, with at least 3+ years in a lead or mentoring role
Strong expertise in SQL, Python, and Spark (PySpark/Scala)
Hands-on experience with modern cloud data platforms such as Snowflake, Databricks, BigQuery, Amazon Redshift
Strong understanding of data modeling methodologies including Kimball and Data Vault

Requirements:

Design, build, and maintain scalable batch and real-time data pipelines
Architect and implement modern Lakehouse solutions using technologies such as Delta Lake or Apache Iceberg
Develop and manage ETL/ELT workflows using tools like Airflow, dbt, or Prefect
Implement robust data quality, governance, lineage, and monitoring frameworks

Evnek

About Evnek

Evnek Technologies strives to be the leader in cloud and analytics services. The insights and quality services we deliver help build trust and confidence in our clients. We develop outstanding relationships with our clients and deliver on our promises. Moreover, we play a crucial role in challenging the traditional technologies and look for opportunities to innovate. Evnek Technologies specializes in Cloud and Enterprise Data Management. We offer services in data integration, business intelligence, data warehousing, architecture, modeling and analytics. We are thought leaders and work with the latest technologies in the Big Data, Cloud, and Data Science space. Evnek Technologies is passionate about adding value. We partner with our clients and ensure a positive user experience all the while building elegant and scalable solutions that evolve with the company and remain dynamic in an ever-changing business landscape.

Founded: 2018

Company size: 11 - 50

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Job description

This is a remote position.

Job Description – Lead Data Engineer
Experience: 7–10 Years
Location: Remote / Hybrid (Bengaluru)
Notice Period: Immediate Joiners Only

Domain:Data Platforms & Analytics Infrastructure

About the Role

We are looking for a highly skilled and experienced Lead Data Engineer to build and scale modern data platforms that power analytics, reporting, and AI/ML initiatives. In this role, you will own the end-to-end data lifecycle, architect scalable data solutions, and lead a team of engineers to deliver reliable, high-performance data infrastructure.

The ideal candidate should have deep expertise in data engineering, distributed processing, cloud platforms, and modern Lakehouse architectures, along with strong leadership and mentoring capabilities.

Key Responsibilities

Design, build, and maintain scalable batch and real-time data pipelines.

Architect and implement modern Lakehouse solutions using technologies such as Delta Lake or Apache Iceberg.

Develop and manage ETL/ELT workflows using tools like Airflow, dbt, or Prefect.

Implement robust data quality, governance, lineage, and monitoring frameworks.

Design optimized data models to support analytics, business intelligence, and ML workloads.

Improve platform scalability, reliability, performance, and cost efficiency.

Collaborate with Analytics, Product, and AI/ML teams to enable data-driven solutions.

Lead and mentor a team of data engineers while driving engineering best practices and standards.

Build and maintain CI/CD pipelines and infrastructure automation for data platforms.

Ensure platform reliability, observability, and operational excellence across the data ecosystem.

Required Skills & Qualifications

7–10 years of experience in Data Engineering, with at least 3+ years in a lead or mentoring role.

Strong expertise in SQL, Python, and Spark (PySpark/Scala).

Hands-on experience with modern cloud data platforms such as: Snowflake ,Databricks ,BigQuery ,Amazon Redshift
Strong understanding of data modeling methodologies including Kimball and Data Vault.