Data Engineer

ADARSH SOLUTIONS PRIVATE LIMITED; Bengaluru; Hybrid; INR 2,500,000 - 3,200,000; Full time

Benefits offered by this job

Medical Insurance

Provident Fund

Certification support

Leadership development

Job summary

ADARSH SOLUTIONS PRIVATE LIMITED is seeking an experienced Databricks data platform engineer to join our specialist team to work on data engineering, data science, geospatial projects, and products. You will design data platform architecture, build pipelines, and ensure alignment with our data architecture standards.

You should have strong cloud knowledge, Databricks platform expertise, and the ability to collaborate with stakeholders to deliver reliable datasets and analytics solutions.

Qualifications

• 36 years of experience as a Data Engineer, Analytics Engineer, or ETL Developer.
• Advanced proficiency in SQL (complex queries, window functions, optimization, performance tuning).
• Strong hands-on experience with Google BigQuery (partitioning, clustering, cost optimization).
• Experience building data pipelines using Databricks (Apache Spark, Delta Lake).
• Solid understanding of ETL/ELT architecture, data warehousing, dimensional modeling, and star/snowflake schemas.
• Experience with Python and/or Scala for data processing and automation.
• Familiarity with cloud platforms such as Google Cloud Platform (GCP), Azure, or AWS.
• Experience with pipeline orchestration tools (Airflow, Databricks Workflows, or similar) preferred.
• Knowledge of data governance, security, IAM, and compliance frameworks is a plus.
• Strong client-facing, communication, and problem-solving skills.
• Ability to work independently in a hybrid or remote work environment.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Databricks, Google BigQuery, SQL, and cloud-native tools.
• Build and optimize batch and streaming data pipelines to support analytics, reporting, and business intelligence use cases.
• Collaborate with business stakeholders, product teams, analytics engineers, and data analysts to gather requirements and deliver data solutions.
• Develop and manage data models, schemas, and transformations ensuring data quality, integrity, and consistency.
• Optimize SQL queries, partitioning, clustering, and indexing for performance and cost efficiency.
• Support BI tools and dashboards by providing clean, reliable, and analytics-ready datasets.
• Implement and monitor data quality checks, validation rules, and error handling across pipelines.
• Troubleshoot and resolve data pipeline failures, performance issues, and data inconsistencies across environments (dev, test, prod).

Skills

SQL proficiency

Google BigQuery

Databricks (Spark)

Python

Scala

Cloud platforms

Airflow

Data governance

Communication skills

Tools

Databricks

Delta Lake

Job description

Overview of Role

We are looking for an experienced Databricks data platform engineer to join our specialist team to work on our Data Engineering, Data Science, Geospatial projects, and products. You will use advanced data engineering, Databricks, cloud services, infrastructure as code, Linux stack, data quality and machine learning to build data platform architecture and solution following our data architecture standards and principles. To succeed in this data platform engineering position, you should have strong cloud knowledge, Databricks platform, analytical skills, the ability to combine data from different sources and develop data pipeline using latest libraries and data platform standards. If you are detail-oriented, with excellent organizational skills and experience in this field, wed like to hear from you.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Databricks, Google BigQuery, SQL, and cloud-native tools.


• Build and optimize batch and streaming data pipelines to support analytics, reporting, and business intelligence use cases.


• Collaborate with business stakeholders, product teams, analytics engineers, and data analysts to gather requirements and deliver data solutions.


• Develop and manage data models, schemas, and transformations ensuring data quality, integrity, and consistency.


• Optimize SQL queries, partitioning, clustering, and indexing for performance and cost efficiency.


• Support BI tools and dashboards by providing clean, reliable, and analytics-ready datasets.


• Implement and monitor data quality checks, validation rules, and error handling across pipelines.


• Troubleshoot and resolve data pipeline failures, performance issues, and data inconsistencies across environments (dev, test, prod).

Ensure compliance with data governance, data security, access controls, and privacy standards. Work directly with clients and external stakeholders to gather requirements, present deliverables, and manage expectations.

Requirements and skills

• 36 years of experience as a Data Engineer, Analytics Engineer, or ETL Developer.


• Advanced proficiency in SQL (complex queries, window functions, optimization, performance tuning).


• Strong hands-on experience with Google BigQuery (partitioning, clustering, cost optimization).


• Experience building data pipelines using Databricks (Apache Spark, Delta Lake).


• Solid understanding of ETL/ELT architecture, data warehousing, dimensional modeling, and star/snowflake schemas.


• Experience with Python and/or Scala for data processing and automation.


• Familiarity with cloud platforms such as Google Cloud Platform (GCP), Azure, or AWS.


• Experience with pipeline orchestration tools (Airflow, Databricks Workflows, or similar) preferred.


• Knowledge of data governance, security, IAM, and compliance frameworks is a plus.


• Strong client-facing, communication, and problem-solving skills.


• Ability to work independently in a hybrid or remote work environment.

What you can expect from us

• We appreciate that individual growth is important as well and we support you on every aspect of personal development.


• Hands-on AWS, Azure, and GCP.


• Support you on any certification.


• Build leadership skills.


• Medical Insurance coverage for self and family.


• Provident Fund.