Senior Backend / AI Systems Engineer, Automated Equity Research

About LH2 AI LabsLH2 AI Labs is an applied research lab solving data platform and curation challenges for foundation model development. We serve every frontier AI lab with the mission of delivering the best data to power the best models.

Our customers are the ones building the foundation models themselves and our work sits directly in the loop of how those systems improve. This is a rare opportunity to join a company at a defining moment in AI.

About the role:

This is a full-time, hands-on role where you will own the core infrastructure and systems that enable us to discover customers' data landscape, handle sensitive data like names, address securely and to clean and catalog them into training-ready datasets.

That path covers connectors and on-prem agentic discovery components, secrets and PII scrubbing, scale and cost efficient ingestion and clearance for use in model training. You lead a small team of 3-4 engineers and raise the quality bar in your pod.

What you'll own

• Connectors and extraction - You'll build connectors for common SaaS and databases (Google Workspace, Slack, Postgres/MySQL, Jira, MongoDB) and for specific tools such as Razorpay, GreytHR, Keka, Zoho and LeadSquared. The rule is to build only where no good open-source connector or clean export exists.
• On-prem scanning - You'll build a CLI or agent that runs at the data owner's end to sample and estimate the value of their data without shipping all of it to us.
• Clearance pipeline - Secrets detection across full git history, fail-closed. PII redaction for code and conversational data, including Indian identifiers (PAN, Aadhaar, GSTIN, IFSC, UPI). Measurable recall and precision.
• Lineage - Every output record must trace back to its raw source, and every lot must be revocable.
• Delivery - Packaging, sampling for buyers, and supporting the supply and BD teams on data questions.

You have

• 8+ years in backend or data engineering, with at least 2 years leading up to 4 or more engineers.
• You've built ingestion or ETL pipelines that run in production.
• Hands-on work with sensitive data such as PII, financial or health data, including redaction, masking or access controls.
• The judgment to decide what to build and what to adopt.

Nice to have

• Experience with Presidio, gitleaks/TruffleHog, dlt or Airbyte.
• Knowledge of DPDP, GDPR, HIPAA or SOC 2.
• You've shipped software that runs in customers' environments.

This is not a pure people-management role. You'll write code, review everything, and personally own the hardest problems in the pod.

About PortOne

PortOne is building the reconciliation and data intelligence layer for payments across Korea and international markets. We are a Series B startup backed by Softbank and Hanwa Capital, powering multi-billion dollars in annualised settlement volume for 2,000+ merchants across Korea, Thailand, Singapore, Indonesia, and beyond.

We are building AI-native products for leading brands — intelligent automation layers on top of complex financial data pipelines. If you want to work at the intersection of fintech, data engineering, and applied AI, this is your role.

Culture and Values

* You will be joining a team that stands for making a difference.

* You will be joining a culture that identifies more with Sports Teams rather than a 9 to 5 workplace.

* Your will have peers who are/have

** Highly Self Driven with A sense of purpose

** High Energy Levels - Building stuff is your sport

** Ownership - Solve customer problems end to end - Customer is your Boss

** Hunger to learn - Highly motivated to keep developing new tech skill sets

Your Work Ethic

* You are an athlete and building apps is your sport.

* Your passion drives you to learn and build stuff and not because your manager tells you to.

* You obsess over correctness — a bug in a settlement figure or a silent data drop is not acceptable to you.

* You have an eye for detail that most engineers skip past, and you take pride in getting it exactly right.

* Your work ethic is that of an athlete preparing for your next marathon. Your sport drives you and you like being in the zone.

* You are NOT a clockwatcher renting out your time, and NOT have an attitude of "I will do only what is asked for"

What will you do?

• Build and maintain financial data ingestion pipelines that pull settlement and transaction data from marketplace platforms (Amazon, Shopee, TikTok, Qoo10, Rakuten) on behalf of large brands operating across multiple Asian markets.
• Own reconciliation workflows end-to-end — from raw marketplace data to verified, merchant-ready settlement reports — ensuring every figure is correct and every discrepancy is surfaced, not swallowed.
• Design and implement AI-native features that automate financial analysis: agentic triage of settlement mismatches, root-cause detection across large transaction volumes, and intelligent alerting for ops and merchant teams.
• Instrument data quality and health monitoring so that silent failures — missing records, schema shifts, delayed ingestion — are caught before they reach the merchant.
• Build APIs and tooling that enable PortOne's ops and merchant success teams to investigate, verify, and close financial discrepancies faster and with more confidence.
• Expand platform coverage by integrating new marketplaces and new report types, working closely with data formats that are often inconsistent, undocumented, or changing without notice.
• Uphold rigorous engineering standards — correctness in financial data is not negotiable, and you treat edge cases and off-by-one errors with the same seriousness as a production incident.
• Uphold high engineering standards across codebases and processes.
• Collaborate with product, design, infrastructure, and operations stakeholders.

Skills and Experience

* Have ideally 4 to 6 Years of experience shipping high quality products/live features and workflows

*AI-native development — you build products where AI is a first-class component, not a bolt-on.

* Strong backend engineering foundation — Go (Preferred), Python, or equivalent; REST/gRPC APIs; database design.

* Understands how to build scalable, resilient, and observable distributed systems.

* Must have built data flows and applications end to end taking full ownership

Preferred Skills and Background

*Prior experience/built apps in golang backend

*Data and data engineering background — comfortable with data pipelines, ETL/ELT patterns, event-driven architectures, reconciliation logic, or analytical workloads.

*AI agentic development — experience building or working with agent frameworks, tool-use patterns, LLM orchestration, or automated reasoning pipelines.

Role Overview:

We are seeking a backend-focused Software Engineer with deep expertise in REST APIs,

real-time integrations, and cloud-based application services. The ideal candidate will build

scalable backend systems, integrate real-time data flows, and contribute to system design

and documentation. This is a hands-on role working with global teams in a fast-paced, Agile

environment.

Key Responsibilities:

• Design, develop, and maintain REST APIs and backend services using Python, FastAPI,

and SQLAlchemy.

• Build and support real-time integrations using AWS Lambda, API Gateway, and

EventBridge.

• Develop and maintain Operational Data Stores (ODS) for real-time data access.

• Write performant SQL queries and work with dimensional data models in PostgreSQL.

• Contribute to cloud-based application logic and data orchestration.

• Containerize services using Docker and deploy via CI/CD pipelines.

• Implement automated testing using pytest, pydantic, and related tools.

• Collaborate with cross-functional Agile teams using tools like Jira.

• Document technical workflows, APIs, and system integrations with clarity and

consistency.

• Should have experience in team management

Required Skills & Experience:

• 8+ years of backend or integrations engineering experience.

• Expert-level knowledge of REST API development and real-time system design.

• Strong experience with: Python (FastAPI preferred), SQLAlchemy.

• PostgreSQL and advanced SQL.

• AWS Lambda, API Gateway, EventBridge.

• Operational Data Stores (ODS) and distributed system integration.

• Experience with Docker, Git, CI/CD tools, and automated testing frameworks.

• Experience working in Agile environments and collaborating with cross-functional

teams.

• Comfortable producing and maintaining clear technical documentation.

• Working knowledge of React is acceptable but not a focus.

• Hands-on experience working with Databricks or similar data platforms.

Education & Certifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field (required).

• Master’s degree is a plus.

• Certifications in AWS (e.g., Developer Associate, Solutions Architect) or Python

frameworks are highly preferred.

Job Description

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop data processing solutions using Python.
• Write complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain data ingestion and integration workflows.
• Implement data quality, validation, monitoring, and error-handling processes.
• Develop and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
• Collaborate with data analysts, data scientists, software engineers, and business teams.
• Optimize data pipelines for performance, reliability, and scalability.
• Troubleshoot production data issues and ensure timely resolution.
• Follow best practices for version control, code quality, testing, and deployment.

Mandatory Skills

• Python
• ETL
• SQL
• CI/CD
• DevOps
• Git / Version Control
• Strong problem-solving and debugging skills

Why this role exists 

Most systems work at a low scale. 

Very few survive real production load, complex workflows, and enterprise edge cases. 

We are building a platform that must: 

1. Scale from 500K → 20M+ interactions/month 
2. Handle complex insurance workflows reliably 
3. Become easier to deploy as it grows, not harder 
4.  
5. This role exists to build the backend foundation that makes this possible. 

What you’ll do 

You will not just write services. 

You will design and own core platform systems. 

1. Scale the platform without breaking architecture 

1. Scale from 50K → 4M+ interactions/month 
2. Ensure: 
3. High availability 
4. Low latency 
5. Fault tolerance 
6. Avoid large rewrites — build systems that evolve cleanly 

2. Build the workflow automation (WA) engine 

1. Design a flexible system with: 
2. States 
3. Stages 
4. Cohorts 
5. Dynamic workflows 
6. Ensure workflows: 
7. Handle edge cases reliably 
8. Can be configured easily 
9. Move from: 
10. Hardcoded flows → configurable execution engine 

3. Build the insurance-specific data layer 

1. Design data models for: 
2. Policy states 
3. Claim workflows 
4. Consent tracking 
5. Ensure the system works across: 
6. Multiple insurers 
7. Multiple use cases 
8. Build a platform-first data layer, not use-case-specific hacks 

4. Make deployment and setup simple 

1. Ensure workflows and data models are: 
2. Easy to configure 
3. Easy to launch 
4. Reduce friction for: 
5. Product teams 
6. Deployment teams 

5. Create a compounding data advantage 

1. Build a data layer that: 
2. Improves with every deployment 
3. Captures structured signals 
4. Ensure data becomes a long-term edge, not just storage 

6. Own production reliability 

1. Participate in on-call rotation across 3 engineers 
2. Ensure: 
3. Incidents are handled quickly 
4. Root causes are fixed permanently 
5. Build systems where reliability is shared, not individual 

What success looks like 

1. Platform scales to 2M+ interactions/month smoothly 
2. Workflow engine supports complex, dynamic use cases 
3. Data layer enables fast deployment across accounts 
4. Edge cases are handled without constant firefighting 
5. System becomes easier to use as it grows 
6. Production issues are rare and predictable 

Who you are 

1. You have built: 
2. Scalable systems 
3. Distributed services 
4. You think in: 
5. Systems 
6. Data models 
7. Trade-offs 
8. You are comfortable owning: 
9. Architecture 
10. Production systems 

What will make you stand out 

1. Experience building: 
2. Workflow engines 
3. State machines 
4. Data-heavy platforms 
5. Strong understanding of: 
6. System design 
7. Distributed systems 
8. Failure handling 
9. Experience working in: 
10. High-scale production environments 

Why join 

1. You will build the core backend of an AI platform 
2. Your work directly impacts: 
3. Scale 
4. Reliability 
5. Product capability 
6. You will design systems that move from: 
7. Use-case specific → platform-level infrastructure 

What this role is not 

1. Not just API development 
2. Not limited to feature-level work 
3. Not disconnected from production realities 

What this role is 

1. A system architect 
2. A builder of scalable platforms 
3. A driver of long-term technical advantage 

One question to self-evaluate 

Can you design backend systems that scale, handle edge cases, and become easier to use as they grow? 

About GeoIQ: 

GeoIQ(a Lenskart subsidiary) is a location intelligence platform that provides comprehensive data and insights to help businesses make informed decisions about their retail operations and expansion. It offers a range of data points, including demographic information, commercial activity, and market performance indicators, to give users a detailed understanding of a specific location or market. 

About the team: 

Our agile team, consisting of 40+ members, is led by a founding team with extensive experience in data analytics, machine learning, and product development. Embrace the opportunity to collaborate with seasoned professionals in a dynamic and innovative work environment. 

Responsibilities: 

• We’re looking for a Backend Engineer who thrives on solving real-world problems and is eager to build scalable, high-performance systems. You should have:
• Keen interest and ability to learn and continuously adapt to the market and technology.
• At least 2–4 years of relevant backend development experience.
• Strong knowledge and experience in Python (Flask) and SQL (we use PostgreSQL and PostGIS).
• Hands-on experience with MongoDB, Airflow and Nginx.
• Practical experience with Cloud Services, including:
• Familiarity with Google Cloud Platform (GCP): Cloud Functions, Cloudbuild, Cloud Storage, Cloud SQL, Cloud Logging, and Cloud Monitoring.
• Familiarity with Kubernetes is a bonus.
• Familiarity with GIS concepts is a plus.
• Strong background in designing and building REST APIs, with the ability to discuss architectural trade-offs and make sound technical decisions.

Why Explore a Career at GeoIQ: 

• Be part of a team that is revolutionizing decision-making for businesses across India.
• Work in a dynamic and innovative environment with ample opportunities for professional growth and learning.
• Contribute to the growth and success of a leading hyperlocal location AI startup in India. 

If you are passionate about creating intuitive and efficient front-end solutions and meet the requirements listed above, we would love to hear from you. Apply now to join our team at GeoIQ!

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

Strong Data Engineer (AWS) Profile

2

Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.

3

Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.

4

Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.

5

Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.

6

Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.

7

Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.

8

Mandatory (Education) – B.Tech / B.E./ M.Tech

Strong Data Engineer (AWS) Profile

2

Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.

3

Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.

4

Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.

5

Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.

6

Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.

7

Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.

8

Mandatory (Education) – B.Tech / B.E./ M.Tech

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.