Lead Data Engineer at Searce Inc · Coimbatore · 7 - 10 years · Profitable · Posted 3 Jun 2026

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.

About Searce Inc
About
What is ‘searce’
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.
What we do
Searce is a modern tech consulting firm that empowers clients to futurify their businesses, leveraging Cloud, AI & Analytics.
- We are a category defining niche’ cloud-native technology consulting company, specializing in modernizing (improve, automate & transform) the full-scope of infra, app, process & work
- We partner with clients in their ‘beyond x’ journey to drive intelligent, impactful & futuristic business outcomes
- We are the most preferred tech partner of choice when it comes to ‘solving for better’ for the new-age tech startups & digital enterprises, leading disruption in their industries
- Our Service Offerings: We offer Advanced Cloud, Data & App Modernization, Cloud Consulting, Management & Improvement (DevOps, SysOps & Cloud Managed Services), Applied AI & Analytics services
- As one of the top 5 niche’ full scope global partners for Google Cloud & a preferred partner for AWS, we are the most preferred ‘engineering-led’ tech company of choice when it comes to solving complex business problems.
Who we are
We are passionate improvers, solvers & futurists. Driven by our engineering excellence mindset, we care most about delivering intelligent, impactful & futuristic business outcomes. Searcians are motivated by continuous improvement & solving for better in everything we do.
At the core, a Searcian is self-driven to become better, everyday. In passionate pursuit of the finest degree of excellence we drive exceptional outcomes in everything we do.
We believe that trust is the most important value. We also believe that we need to ‘earn the trust’, everytime one engages with us. And earning trust for us is far more important than anything else. We aim to be the *most trusted* tech consulting partner for our clients.
We are HAPPIER at heart. Humble, Adaptable, Positive, Passionate, Innovative, Excellence focused, & Responsible. We live the HAPPIER Culture Code.
Being HAPPIER.
How we work
- Customers. Partners. Our aim is to build relationships with customers for life. And meaningfully improve the life of every customer.
- We do what we say. We say what we do. We are uncomfortably honest and transparent. Being genuine wins trust & makes people happier.
- Mistakes are encouraged. We make mistakes. Tons of those. Everyday. And we don’t mind apologizing to our juniors, peers or superiors. We are no ego-doers.
- Underpromise. Overdeliver. We work with a deep desire to go above and beyond in everything we do. Everytime.
So, If you are passionate about tech, future & what you read above (we really are!), apply here to experience the ‘Art of Possible’
Connect with the team
Similar jobs (10)
Experience: 6+ years overall Data Engineering experience.
Must-have — candidates should have hands-on experience in ALL of these:
- GCP (Google Cloud Platform) – strong hands-on experience
- Python – data engineering/ETL development
- SQL – advanced SQL, query optimization, data transformation
- BigQuery – strong hands-on experience with development, optimization and data warehousing
- Data Engineering / ETL – building and maintaining data pipelines
- GCP data services – preferably Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow, etc.
- Data warehousing / dimensional modeling
Job Description:
Position: Lead / Senior Data Engineer
Location: Chennai
Shift: US Eastern Time ( 5:00 PM – 2:00 AM )
Experience : 8+ years
Notice Period: Immediate Joiner only
Roles and Responsibilities:
Role Overview
The Lead Data Engineer will be responsible for designing, developing, and delivering high-quality software and data solutions while leading a team of engineers. The role involves hands-on technical work, architectural decision-making, mentoring junior developers, and collaborating with cross-functional teams to ensure successful delivery of scalable data platforms and analytical solutions.
Key Responsibilities:
Lead the end-to-end design, development, and delivery of software systems, data pipelines, and components.
Define technical strategy, architecture, and best practices for development and data engineering.
Design and build optimized data pipelines using cutting-edge technologies in a cloud environment.
Construct infrastructure for efficient ETL processes from various sources and storage systems.
Architect, design, and maintain database pipeline architectures, ensuring readiness for AI/ML transformations.
Lead the implementation of algorithms and prototypes to transform raw data into useful information.
Review code for quality, scalability, and performance.
Collaborate with Product Managers, Business Managers, Designers, and QA teams to translate business requirements into technical solutions.
Develop analytical tools, programs, and reporting mechanisms.
Create data validation methods and data analysis tools.
Interpret data trends and patterns to establish operational alerts.
Conduct complex data analysis and present results effectively.
Prepare data for prescriptive and predictive modeling.
Ensure compliance with data governance and security policies.
Troubleshoot, debug, and resolve complex technical issues.
Drive continuous improvement in software and data development processes, tools, and methodologies.
Mentor and guide engineers through code reviews, technical discussions, and training.
Ensure timely delivery of projects while maintaining high engineering standards.
Continuously explore opportunities to enhance data quality and reliability.
Apply strong programming and problem-solving skills to develop scalable solutions.
Demonstrate passion for testing strategy, problem-solving, and continuous learning.
Willingness to acquire new skills and knowledge.
Possess a product/engineering mindset to drive impactful data solutions.
Experience working in distributed environments with global teams.
Stay current with emerging technologies and industry trends to propose innovative solutions.
Technical Skills and Experience Requirements
Minimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.
High proficiency in Python, Scala, and Spark for applied large-scale data processing.
Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.
Solid understanding of batch and streaming data processing techniques.
Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.
Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
Experience with RDBMS and OLAP databases such as MySQL and Snowflake.
Familiarity with Agile methodologies.
Obsession for service observability, instrumentation, monitoring, and alerting.
Knowledge or experience in architectural best practices for building data lakes.
Qualifications - Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
Skills Referential (Required knowledge, skills and abilities)
Technical Skills:
Python
Pyspark
SQL
ETL Aws, Azure, gcp
Senior Data Engineer – Ab Initio | GCP | Spark | Agentic AI
Location: Bangalore
Experience: 5+ Years
Role: Senior Data Engineer
Work Mode: Bangalore
Job Summary
We are looking for an experienced Senior Data Engineer with strong expertise in Ab Initio, GCP, Apache Spark, and Agentic AI. The ideal candidate will have hands-on experience designing and developing scalable data engineering solutions, building data pipelines, and working with modern cloud and AI technologies.
The candidate should be comfortable working across traditional enterprise data platforms and emerging Generative AI / Agentic AI solutions.
Key Responsibilities
- Design, develop, and maintain scalable and high-performance data pipelines using Ab Initio, Spark, and GCP services.
- Develop and optimize complex ETL/ELT workflows using Ab Initio.
- Build and maintain data processing solutions using Apache Spark / PySpark.
- Develop cloud-based data solutions on Google Cloud Platform (GCP).
- Work with GCP data services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, or equivalent services.
- Perform data integration, transformation, cleansing, and validation.
- Optimize data pipelines for performance, scalability, reliability, and cost.
- Collaborate with data architects,
About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.
Key Responsibilities:
- Design, develop, test, and maintain optimal data pipeline and ETL architectures.
- Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
- Prepare and optimize data for predictive and prescriptive modeling.
- Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
- Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
- Utilize big data tools and frameworks to optimize data acquisition and preparation.
- Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
- Develop and curate data models for analytics, dashboards, and reports.
- Conduct code reviews, maintain production-level code, and implement testing approaches.
- Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
- Drive innovation and implement efficient new approaches to data engineering tasks.
Must-Have Skills:
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
- 3–5 years of experience designing and implementing data warehouse solutions.
- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
- Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
- Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
- Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
- Strong problem-solving, communication, and collaboration skills.
Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
Competencies:
- Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
- Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
Data Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
What you'll need
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
- 5+ years of professional data engineering experience.
- Experience designing and building cloud-native data solutions.
- Strong expertise with Google Cloud Platform, including BigQuery. Experience developing transformation frameworks using dbt.
- Strong SQL and Python programming skills.
- Experience with PostgreSQL or other relational databases.
- Experience orchestrating workflows using Apache Airflow or Cloud Composer.
- Experience implementing Infrastructure as Code using Terraform. Experience building CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar platforms.
- Experience developing scalable batch and streaming data pipelines. Strong problem-solving skills with the ability to balance scalability, reliability, and cloud cost optimization.
Preferred Qualifications
- Experience with Pub/Sub, Datastream, Dataflow, Cloud Storage, Cloud Functions, or Cloud Run.
- Experience building multi-tenant SaaS platforms.
- Experience implementing metadata-driven governance, lineage, and data quality frameworks.
- Experience supporting AI, machine learning, or customer-facing analytics platforms.
- Experience with Kubernetes and Docker.
Description
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.
Job Description: Python + AI
Company: Wissen Technology
Location: Bangalore, India
Experience: 5+Years
Employment Type: Full-Time
Role: Python + AI / Data Engineer
About the Role
Wissen Technology is looking for experienced Python + AI / Data Engineering professionals to join our technology team in Bangalore. The ideal candidate will have strong hands-on experience in Python, Artificial Intelligence, Generative AI, PySpark, Snowflake, and data pipeline development.
The candidate should be capable of designing and developing scalable data and AI solutions, building robust ETL/ELT pipelines, working with large datasets, and integrating AI/ML capabilities into enterprise applications.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python and PySpark.
- Develop robust ETL/ELT pipelines for processing large volumes of structured and unstructured data.
- Build and optimize data processing solutions using Apache Spark / PySpark.
- Develop data ingestion and transformation pipelines into Snowflake.
- Design and implement scalable Snowflake data models, tables, views, and SQL transformations.
- Work with batch and, where applicable, real-time data processing pipelines.
- Build and integrate AI and Generative AI solutions using Python.
- Develop LLM-based applications, RAG solutions, AI agents, and AI-powered services.
- Integrate AI models with enterprise data platforms and data pipelines.
- Develop REST APIs and microservices using FastAPI, Flask, or Django.
- Perform data cleansing, transformation, validation, and quality checks.
- Optimize PySpark jobs, SQL queries, Snowflake workloads, and data pipelines for performance and scalability.
- Implement data pipeline monitoring, logging, error handling, and alerting.
- Work with cloud platforms such as AWS, Azure, or GCP.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders.
- Participate in technical design, architecture, code reviews, and production support.
- Mentor junior engineers and contribute to engineering best practices.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related field.
- Experience working on enterprise-scale AI and data engineering projects.
- Experience combining Python + PySpark + Snowflake + AI/GenAI in production environments.
- Experience with Databricks is an advantage.
- Experience with AI Agents / Agentic AI and tool/function calling.
- Knowledge of distributed systems and cloud-native architecture.
- Experience leading technical initiatives or mentoring engineering teams.
Job Summary
Role Overview
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.
Experience with Google Cloud Platform (GCP) will be an added advantage.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
- Develop complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain reliable data integration workflows across multiple data sources.
- Perform data cleansing, validation, transformation, and quality checks.
- Analyze data and provide insights to support business and technical requirements.
- Implement and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
- Troubleshoot data pipeline failures, performance issues, and production incidents.
- Optimize data processing workflows for performance, scalability, and reliability.
- Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
- Follow best practices for version control, testing, documentation, and deployment.
- Contribute to cloud-based data engineering initiatives, preferably on GCP.
Required Skills
- 5–7 years of hands-on experience in Data Engineering.
- Strong programming skills in Python.
- Strong expertise in Advanced SQL and database concepts.
- Hands-on experience with ETL/ELT processes and data pipelines.
- Good understanding of Data Warehousing and Data Modeling concepts.
- Experience with CI/CD practices and tools.
- Strong understanding of DevOps principles, automation, and deployment processes.
- Strong data analytics and problem-solving skills.
- Experience working with large datasets and performance optimization.
- Good understanding of Git/version control and software development best practices.
Good to Have
- Hands-on experience with Google Cloud Platform (GCP).
- Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
- Experience with containerization/orchestration technologies such as Docker/Kubernetes.
- Experience with workflow orchestration tools such as Airflow.
- Knowledge of cloud-based data architecture and distributed data processing.
Preferred Candidate Profile
- Strong analytical and problem-solving abilities.
- Good communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Strong ownership of data pipelines and production systems.
- Candidates who can join at short notice are preferred.
Mandatory Skills
Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops






