Manager - Data Engineering at Searce Inc · Coimbatore · 7 - 10 years · Profitable · Posted 30 Apr 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.
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
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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.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
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1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
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Bang/hyderabad
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About Solutionara
Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.
Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.
As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.
Every team member is expected to think like a consultant and business problem solver—understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.
AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.
Role Overview
Solutionara is seeking a Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.
This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.
Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years
Key Responsibilities
Data Engineering
- Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
- Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
- Develop high-quality SQL and Python-based data processing solutions.
- Implement batch and incremental data-processing patterns.
- Develop reusable engineering components and frameworks.
- Support complex data migration and transformation activities.
- Perform source-to-target mapping and technical data analysis.
- Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.
Database & Platform Engineering
- Design and optimize relational database schemas and data structures.
- Analyze and improve SQL/query performance.
- Support indexing, partitioning, storage optimization, and database performance.
- Implement appropriate database security and access controls.
- Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
- Troubleshoot database and pipeline performance issues.
- Contribute to cloud data-platform configuration and optimization.
Data Quality
- Implement automated validation and data-quality controls.
- Develop reconciliation processes between source and target systems.
- Identify duplicate, incomplete, inconsistent, and invalid data.
- Implement cleansing, standardization, validation, and exception-management logic.
- Work with technical and business stakeholders to understand and implement business data rules.
Technical Delivery
- Convert technical designs into reliable production solutions.
- Participate in technical design and code reviews.
- Mentor junior/mid-level engineers.
- Support estimation and technical planning.
- Troubleshoot complex production and integration issues.
- Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
- Document technical designs, mappings, configurations, operational procedures, and engineering decisions.
Consulting & AI-Led Working
- Understand the business purpose behind assigned engineering requirements.
- Raise risks, assumptions, dependencies, and potential improvements proactively.
- Communicate effectively with client and internal stakeholders.
- Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
- Independently verify AI-generated code and recommendations before implementation.
- Identify opportunities for engineering automation and process improvement.
Required Qualifications
- 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
- Advanced SQL skills.
- Strong hands-on Python experience.
- Strong ETL/ELT development experience.
- Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
- Experience with data modeling and database design.
- Experience with AWS, Azure, or another major cloud platform.
- Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
- Experience with performance tuning and optimization.
- Experience with data validation and reconciliation.
- Strong troubleshooting and analytical skills.
- Ability to take ownership of engineering deliverables with limited supervision.
Preferred Qualifications
- Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
- Experience with manufacturing, retail, distribution, or consumer-goods data.
- Experience with CI/CD and infrastructure/platform engineering practices.
- Experience with API and event-driven integrations.
- Previous consulting or technology-services experience.
What Success Looks Like
- Pipelines and databases perform reliably at enterprise scale.
- Engineering solutions are maintainable, reusable, and well documented.
- Data issues are detected and addressed systematically.
- Junior engineers receive effective technical guidance.
- Problems are owned through resolution rather than simply escalated.
- Engineering decisions reflect both technical requirements and client business objectives.
About the Role
You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.
Key Responsibilities
- Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
- Design and optimize data models for AI and machine learning workloads.
- Develop reliable data foundations for MLOps, governance, and data lineage.
- Integrate data from multiple sources into modern data platforms.
- Leverage Snowpark ML and Snowflake's native AI capabilities.
- Ensure data platforms are secure, scalable, and high-performing.
What We're Looking For
- 5+ years of hands-on experience with Snowflake.
- Strong proficiency in SQL and Python.
- Experience with AWS, Azure, or GCP.
- Knowledge of cloud storage services such as S3, ADLS, or GCS.
- Strong understanding of Dimensional Modeling and Data Vault.
- Experience with Scala or Java is a plus.
Tech Stack
- Data Warehouse: Snowflake
- Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
- Cloud: AWS, Azure, GCP
- Storage: S3, ADLS, GCS
- AI/ML: Snowpark ML, MLOps
Perks & Benefits
- Public Speaking & Communication Program
- Mentoring Program with Senior Support Leads
- 360° Progress Reviews
- Weekly Learning Sessions & Guilds
- Paid Certifications
- Hackathons & Innovation Days
- Recognition & Rewards Programs
- Team Socials & Annual Offsites
- Employee Assistance Program (24/7 Wellbeing Support)
The Data People Shaping Tomorrow
Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.
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!
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,
Responsibilities and JD
Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.










