Digital Marketing Head

Lead Data Engineer

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

Your Responsibilities

What you will wake up to solve.

• Lead Technical Design & Data Architecture: Architect and lead the end-to-end development of scalable, cloud-native data platforms. You’ll guide the squad on critical architectural decisions—choosing between Batch vs. Streaming or ETL vs. ELT—while remaining 100% hands-on, contributing high-quality, production-grade code.
• Build High-Velocity Data Pipelines: Drive the implementation of robust data transports and ingestion frameworks using Python, SQL, and Spark. You will build integration layers that connect heterogeneous sources (SaaS, RDBMS, NoSQL) into unified, high-availability environments like BigQuery, Snowflake, or Redshift.
• Mentor & Elevate the Squad: Foster a culture of technical excellence by mentoring and inspiring a team of data analysts and engineers. Lead deep-dive code reviews, promote best-practice data modeling (Star/Snowflake schema), and ensure the squad adopts modern engineering standards like CI/CD for data.
• Drive AI-Ready Data Strategy: Be the expert in designing data foundations optimized for AI and Machine Learning. You will champion the use of GCP (Dataflow, Pub/Sub, BigQuery) and AWS (Lambda, Glue, EMR) to create "clean room" environments that fuel advanced analytics and generative AI models.
• Partner with Clients as a Technical DRI: Act as the Directly Responsible Individual for client success. Translate ambiguous business questions into elegant data services, manage project deliverables using Agile methodologies, and ensure that the data provided is accurate, consistent, and mission-critical.
• Troubleshoot & Optimize for Scale: Own the reliability of the reporting layer. You will proactively monitor pipelines, troubleshoot complex transformation bottlenecks, and propose ways to improve platform performance and cost-efficiency.
• Innovate and Build Reusable IP: Spearhead the creation of reusable data frameworks, custom operators, and transformation libraries that accelerate future projects and establish Searce’s unique technical advantage in the market.

Welcome to Searce

The AI-Native tech consultancy that's rewriting the rules.

Searce is an AI-native, engineering-led, modern tech consultancy that empowers clients to futurify their business by delivering intelligent, impactful, real business outcomes. Searce solvers co-innovate with clients as their trusted transformational partners ensuring sustained competitive advantage. Searce clients realize smarter, faster, better business outcomes delivered by AI-native Searce solver squads. 

Functional Skills 

the solver personas.

• The Data Architect: This persona deconstructs ambiguous business goals into scalable, elegant data blueprints. They don't just move data; they design the foundation—from schema design to partitioning strategies—that allows data scientists and analysts to thrive, foreseeing technical bottlenecks and making pragmatic trade-offs.
• The Player-Coach: As a hands-on leader, this persona leads from the front by writing exemplary, production-grade SQL and Python while simultaneously mentoring and elevating the skills of the squad. Their success is measured by the team's ability to deliver high-quality, maintainable code and their growth as engineers.
• The Pragmatic Innovator: This individual balances a passion for modern data tech (like Generative AI and Real-time Streaming) with a sharp focus on business outcomes. They champion new tools where they add real value but are disciplined enough to choose stable, cost-effective solutions to meet deadlines and deliver robust products.
• The Client-Facing Technologist: This persona acts as the crucial technical bridge between the data squad and the client. They build trust by listening actively, explaining complex data concepts (like data latency or idempotency) in simple terms, and demonstrating how engineering decisions align with the client’s strategic goals.
• The Quality Craftsman: This individual possesses an unwavering commitment to data integrity and treats data engineering as a craft. They are the guardian of the reporting layer, advocating for robust testing, data validation frameworks, and clean, modular code to ensure the long-term reliability of the data platform.

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

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Pay: ₹70,000.00 - ₹90,000.00 per month

Job description:

Name of the College: KGiSL Institute of Technology

College Profile: The main objective of KGiSL Institute of Technology is to provide industry embedded education and to mold the students for leadership in industry, government, and educational institutions; to advance the knowledge base of the engineering professions; and to influence the future directions of engineering education and practice. The ability to connect to the future challenges and deliver industry-ready human resources is a credibility that KGISL Educational Institutions have progressively excelled at. Industry -readiness of its students is what will eventually elevate an institution to star status and its competitiveness in the job market. Choice of such an institution will depend on its proximity to industry, the relevance of its learning programme to real-time industry and the active connect that a student will have with industry professionals.

Job Title: Assistant Professor / Associate Professor

Departments:

● CSE

Qualification:

● ME/M.Tech/Ph.D(Ph.D must for Associate Professor)

Experience:

● Experience - 9-10 Years

Key Responsibilities:



1. Teaching & Learning:

Deliver high-quality lectures and laboratory sessions in core and advanced areas of Computer Science & Engineering.

Prepare lesson plans, teaching materials, and assessment tools as per the approved curriculum.

Adopt innovative teaching methodologies, including ICT-enabled learning and outcome-based education (OBE).

2. Research & Publications:

Conduct independent and collaborative research in areas of specialization.

Publish research papers in peer-reviewed journals and present in reputed conferences.

Eligibility & Qualifications (As per AICTE/UGC Norms):

Educational Qualification: Ph.D. in Computer Science & Engineering or relevant discipline.

Experience: Minimum of 9 years teaching/research/industry experience, with at least 3 years at the level of Assistant Professor.

Research: Minimum of 7 publications in refereed journals as per UGC-CARE list and at least one Ph.D. degree awarded or ongoing under supervision.

Other Requirements:

1. Good academic record throughout.
2. Proven ability to attract research funding.
3. Strong communication and interpersonal skills.
4. Work Location: [ KGiSL Campus]
5. Employment Type: Full-time / Permanent
6. Joining time: immediately

Job Type: Full-time

Benefits:

• Health insurance
• Life insurance
• Provident Fund

Work Location: In person

Experience in TeleSales, Telemarketing, B2B Sales, B2C Sales.

● Good Communication Skills

● Good Convincing Skills

● Flexible with working days and times

Communication: Excellent communication skills in English and/or any regional language(

Hindi, Marathi, Malayalam, Tamil, Gujarati)

● Agility: Ability to change according to business requirements.

● Motivation: Demonstrate a positive, ‘can-do’ attitude. Willing to roll up your sleeves and

● get things done.

● Data-driven: Keen interest in analyzing performance data and transforming it into actionable

strategies.

● Growth-driven: Keen to grow as an individual

• Identify and assess customers’ needs to achieve satisfaction
• Build sustainable relationships and trust with customer accounts through open and interactive communication
• Provide accurate, valid and complete information by using right methods/tools
• Follow communication procedures, guidelines and policies
• Take the extra mile to engage customers
• Keep records of customer interactions
• Making calls on Decline Users and understanding the reason behind it
• Converting of Decline users to business.
• Generating leads for the business via online or offline mode
• Making more people aware about the product
• Reaching out to customers and make them Register and avail the loan.
• Expanding the business by Marketing and Branding
• Making 200 + connected calls everyday

Job Role:  Senior Software Developer (React native/React js)

Required Skills

• React Native minimum experience should be 3 YRS.
• 2+ years of experience in javascript. 
• Minimum 2 years of experience in Typescript and ReactJs. 
• React-native components Knowledge and Redux. 
• Design Layout knowledge 
• Good communication