Databricks Data Engenieer

Company Description

At AbsoluteLabs, we strive to deliver exceptional business outcomes by transforming complex challenges into opportunities. With a history rooted in high-end retail technology consultancy, we have grown into trusted partners for clients across various sectors. Our team of experts is dedicated to fostering innovation and collaboration, helping businesses adapt and thrive in the ever-evolving digital era. We are steadfast in supporting clients as they navigate technological advancements, market trends, and the demands of modern consumers.

Role Summary:

We are seeking a Data Engineer with strong expertise in Databricks and large-scale data engineering to design, build, and optimize our data lakehouse solutions. The ideal candidate will be hands-on with PySpark, SQL, Delta Lake, and cloud data platforms, and will play a key role in enabling data-driven decision-making across the organization.

Key Responsibilities

• Design, develop, and maintain

  scalable ETL/ELT pipelines

  using Databricks and PySpark.
• Implement and optimize data ingestion from multiple structured and unstructured sources (APIs, databases, streaming data, cloud storage).
• Build and manage

  Delta Lake

  architectures for data lakehouse solutions.
• Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data sets for analytics and ML models.
• Ensure

  data quality, governance, and security compliance

  across the data lifecycle.
• Optimize Databricks workloads for performance, cost efficiency, and scalability.
• Implement CI/CD pipelines for data engineering workflows using tools like Git, Azure DevOps, or Jenkins.
• Monitor, troubleshoot, and resolve issues in data pipelines and platform operations.

Skill & Qualification:

• 5 - 8 years of experience in Data Engineering, with minimum 3+ years in Databricks.
• Expert in PySpark, SQL, Delta Lake, and advanced Databricks features.
• Strong experience with at least one cloud platform (Azure, AWS, or GCP) and its data services (e.g., ADF, Glue, BigQuery, Redshift, Synapse)
• Hands-on experience in ETL/ELT, data modeling, and performance tuning.
• Proficiency in Git, DevOps practices, and CI/CD workflows.
• Solid understanding of data security, lineage, and governance frameworks.