4+ Data engineering Jobs in Coimbatore | Data engineering Job openings in Coimbatore

Who are we ?

Searce means ‘a fine sieve’ & indicates ‘to refine, to analyze, to improve’. It signifies our way of working: To improve to the finest degree of excellence, ‘solving for better’ every time. Searcians are passionate improvers & solvers who love to question the status quo.

The primary purpose of all of us, at Searce, is driving intelligent, impactful & futuristic business outcomes using new-age technology. This purpose is driven passionately by HAPPIER people who aim to become better, everyday.

Tech Superpowers

End-to-End Ecosystem Thinker: You build modular, reusable data products across ingestion, transformation (ETL/ELT), and consumption layers. You ensure the entire data lifecycle is governed, scalable, and optimized for high-velocity delivery.

The MDS Architect. You reimagine business with the Modern Data Stack (MDS) to deliver Data Mesh implementations and real value. You treat every dataset as a measurable "Data Product with a clear focus on ROI and time-to-insight.

Distributed Compute & Scale Savant: You craft resilient architectures that survive petabyte scale volume and data skew without "breaking the bank. You prove your designs with cost-performance benchmarks, not just slideware.

Al-Ready Orchestrator: You engineer the bridge between structured data and Unstructured/Vector stores. By mastering pipelines for RAG models and GenAl, you turn raw data into the fuel for intelligent, automated workflows.

The Quality Craftsman (Builder @ Heart): You are an outcome-focused leader who lives in the code. From embedding GDPR/PII privacy-by-design to optimizing SQL, Python, and Spark daily, you ensure integrity is baked into every table

Experience & Relevance

Engineering Depth: 7-10 years of professional experience in end-to-end data product development. You have a portfolio that proves your ability to build complex, high-velocity pipelines for both Batch and Streaming workloads

Cloud-Native Fluency: Deep, hands-on experience designing and deploying scalable data solutions on at least one major cloud platform (AWS, GCP, or Azure). You are comfortable navigating the nuances of EMR, BigQuery, or Synapse at scale.

Al-Native Workflow: You don't just build for Al you build with Al. You must be proficient in using Al coding assistants (e.g.. GitHub Copilot) to accelerate your delivery and have a track record of building the data foundations required for Generative Al.

Architectural Portfolio: Evidence of leading 2-3 large-scale transformations-including platform migrations, data lakehouse builds, or real-time analytics architectures.

Foster a culture of technical excellence by mentoring and inspiring a team of Data analysts and engineers. Lead deep-dive code reviewa, prompte best-practice data modeling and ensure the squad adopts modern engineering standards like CI/CD For data

Client-Facing Acumen: You have direct experience in a consultative, client-facing role. You can confidently translate a CEO's business vision into a Lead Engineer's technical specification without losing anything in translation.

The "Solver" Mindset: A track record of solving 'impossible data problems-whether it's fixing massive data skew, optimizing spiraling cloud costs, or architecting 99.9% available data services.

Who are we ?

Searce means ‘a fine sieve’ & indicates ‘to refine, to analyze, to improve’. It signifies our way of working: To improve to the finest degree of excellence, ‘solving for better’ every time. Searcians are passionate improvers & solvers who love to question the status quo.

The primary purpose of all of us, at Searce, is driving intelligent, impactful & futuristic business outcomes using new-age technology. This purpose is driven passionately by HAPPIER people who aim to become better, everyday.

Tech Superpowers

End-to-End Ecosystem Thinker: You build modular, reusable data products across ingestion, transformation (ETL/ELT), and consumption layers. You ensure the entire data lifecycle is governed, scalable, and optimized for high-velocity delivery.

The MDS Architect. You reimagine business with the Modern Data Stack (MDS) to deliver Data Mesh implementations and real value. You treat every dataset as a measurable "Data Product with a clear focus on ROI and time-to-insight.

Distributed Compute & Scale Savant: You craft resilient architectures that survive petabyte scale volume and data skew without "breaking the bank. You prove your designs with cost-performance benchmarks, not just slideware.

Al-Ready Orchestrator: You engineer the bridge between structured data and Unstructured/Vector stores. By mastering pipelines for RAG models and GenAl, you turn raw data into the fuel for intelligent, automated workflows.

The Quality Craftsman (Builder @ Heart): You are an outcome-focused leader who lives in the code. From embedding GDPR/PII privacy-by-design to optimizing SQL, Python, and Spark daily, you ensure integrity is baked into every table

Experience & Relevance

Engineering Depth: 7-10 years of professional experience in end-to-end data product development. You have a portfolio that proves your ability to build complex, high-velocity pipelines for both Batch and Streaming workloads

Cloud-Native Fluency: Deep, hands-on experience designing and deploying scalable data solutions on at least one major cloud platform (AWS, GCP, or Azure). You are comfortable navigating the nuances of EMR, BigQuery, or Synapse at scale.

Al-Native Workflow: You don't just build for Al you build with Al. You must be proficient in using Al coding assistants (e.g.. GitHub Copilot) to accelerate your delivery and have a track record of building the data foundations required for Generative Al.

Architectural Portfolio: Evidence of leading 2-3 large-scale transformations-including platform migrations, data lakehouse builds, or real-time

analytics architectures.

Client-Facing Acumen: You have direct experience in a consultative, client-facing role. You can confidently translate a CEO's business vision into a Lead Engineer's technical specification without losing anything in translation.

The "Solver" Mindset: A track record of solving 'impossible data problems-whether it's fixing massive data skew, optimizing spiraling cloud costs, or architecting 99.9% available data services.

Job Summary:

Seeking an experienced Senior Data Engineer to lead data ingestion, transformation, and optimization initiatives using the modern Apache and Azure data stack. The role involves working on scalable pipelines, large-scale distributed systems, and data lake management.

Core Responsibilities:

· Build and manage high-volume data pipelines using Spark/Databricks.

· Implement ELT frameworks using Azure Data Factory/Synapse Pipelines.

· Optimize large-scale datasets in Delta/Iceberg formats.

· Implement robust data quality, monitoring, and governance layers.

· Collaborate with Data Scientists, Analysts, and Business stakeholders.

Technical Stack:

· Big Data: Apache Spark, Kafka, Hive, Airflow, Hudi/Iceberg

· Cloud: Azure (Synapse, ADF, ADLS Gen2), Databricks, AWS (Glue/S3)

· Languages: Python, Scala, SQL

· Storage Formats: Delta Lake, Iceberg, Parquet, ORC

· CI/CD: Azure DevOps, Terraform (infra as code), Git

Senior Data Engineer (Apache Stack + Databricks/Synapse)

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Thirega@ vysystems dot com - WhatsApp - 91Five0033Five2Three

• Must have the experience of leading teams and drive customer interactions
• Must have multiple successful deployments user stories
• Extensive hands on experience in Apache Spark along with HiveQL
• Sound knowledge in Amazon Web Services or any other Cloud environment.
• Experienced in data flow orchestration using Apache Airflow
• JSON, XML, CSV, Parquet file formats with snappy compression.
• File movements between HDFS and AWS S3
• Experience in shell scripting and scripting to automate report generation and migration of reports to AWS S3
• Worked in building a data pipeline using Pandas and Flask FrameworkGood Familiarity with Anaconda and Jupyternotebook