Associate Instructor (SDE, DBMS),

Data Engineer

Location: Bengaluru, India (Hybrid)

Employment Type: Full-time

Experience: 3-5 years

Role Overview  

What We’re Looking For:

• Bachelor’s degree in Computer Science/Engineering or equivalent experience required.
• Experience designing and shipping cloud services products.
• Experience driving and managing technical and architectural dependencies on AWS Cloud.
• A firm understanding of system architecture, cloud computing, PaaS/SaaS design principles, S3, DynamoDB, RDS mandatory.
• Experience in building or maintaining ETL processes and tools, i.e., AWS Glue or any open-source tool.
• Proven system-level design contribution to a current “Live” (in production / under daily high load) multi-region SaaS or PaaS offering.
• Proven experience with S3, DynamoDB, SQL, and AWS RDS services.
• Proficiency in programming languages such as Python.
• Strong analytical and problem-solving skills.
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Required Skills & Experience

• Experience with Python, SQL, and data visualization/exploration tools.
• Familiarity with the AWS ecosystem, specifically S3, DynamoDB, and RDS.
• Communication skills, especially for explaining technical concepts to nontechnical business leaders.
• Ability to work on a dynamic, research-oriented team that has concurrent projects.
• Experience in AWS cost optimization (Savings Plans, Reserved Instances, Spot Instances) and governance frameworks.
• Experience developing solutions using infrastructure orchestration tools (SSM, automation account, Ansible, etc.).
• Excellent leadership, stakeholder management, and communication skills.

What We Offer

• Work with some of the brightest minds in the emerging EV industry.
• Make a tangible impact in reducing carbon emissions and enabling sustainable energy.
• Freedom to suggest, implement, and innovate on systems, processes, and technologies.
• Daily ownership in a high-growth, challenging environment.
• Flexible work environment with hybrid schedules and virtualization options.
• Competitive pay and benefits including health coverage, innovative PTO program, and performance bonuses.

Data Platform Engineer

Design, automate, and scale our data platform — this is an engineering role, not a traditional "DBA job.

Must-have :

• Data modeling & schema design (from first principles, not just maintenance)
• PostgreSQL (deep, hands-on — partitioning, replication, tuning)
• Any distributed NoSQL store (Cassandra, ScyllaDB, or similar wide-column/distributed DB) (real production experience)
• Python (automation & tooling, not just scripting)
• DevOps & CI/CD (building pipelines, not just using them)
• Terraform (infrastructure-as-code)

You'll:

• Design schemas, partitioning strategies, and lead the Postgres → Cassandra migration end-to-end
• Own PostgreSQL performance, replication, and zero-downtime schema changes
• Build Python-based automation to eliminate repetitive DB work
• Own CI/CD pipelines and Terraform-based infra provisioning
• Drive uptime, DR, monitoring, and incident response
• Own multi-tenant security (RLS, least-privilege access) and data governance

Experience: 4–9 years, data/database/platform engineering in demanding production environments.

Bonus: Kafka/Debezium (CDC), Redis, Flyway/Liquibase, GDPR/DPDP exposure.

Qualifications

● 3-8 years experience in Cloud Database Administration

● Proficient in PostgreSQL database management, including installation, configuration, and performance tuning.

● Experience with Amazon RDS or Cloud SQL and managing databases in cloud environments.

● Proficient in PostgreSQL/MySQL database management, including installation, configuration, and performance tuning.

● Proven experience as a Database Administrator with a focus on

PostgreSQL/MySQL.

● In-depth knowledge of database design, implementation, and management for both PostgreSQL/MySQL environments.

● Familiarity with database security, backup procedures, and performance tuning for both systems.

● Strong analytical and problem-solving skills.

● Excellent communication and collaboration abilities.

● Relevant certifications (e.g., PostgreSQL Certified Professional, MySQLDatabase Administrator) are a plus.

Skills:

● Expertise in PostgreSQL/MySQL database management systems.

● SQL programming and query optimization for both databases.

● Data modeling and database design for PostgreSQL/MySQL.

● Backup and recovery procedures for both environments.

● Performance tuning and optimization for PostgreSQL/MySQL.

● Security protocols and measures for PostgreSQL/MySQL.

● Capacity planning and scalability for both systems.

We are looking for a Database Engineer (PostgreSQL) with 1-5 years of experience to manage, optimize, and maintain PostgreSQL databases. The ideal candidate will have expertise in PostgreSQL, SQL Optimization, Database Design, Performance Tuning, Data Migration, and Backup & Recovery.

Responsibilities:

• Design, develop, and maintain PostgreSQL databases.
• Optimize SQL queries and improve database performance.
• Perform database design, indexing, and schema management.
• Execute data migration, backup, recovery, and disaster recovery activities.
• Monitor database health and troubleshoot performance issues.
• Collaborate with development teams to ensure scalable database solutions.

Requirements:

• 1-5 years of PostgreSQL database experience.
• Strong SQL and performance tuning skills.
• Knowledge of database backup, recovery, and migration processes.

We are looking for an AWS Data Engineer to build reliable, scalable data pipelines on AWS.

Responsibilities

• Build ETL and ELT pipelines with AWS Glue and dbt
• Model and optimise data warehouses in Redshift and Snowflake
• Orchestrate workflows with Apache Airflow
• Build streaming ingestion with Amazon Kinesis
• Ensure data quality, monitoring and cost efficiency

Requirements

• 2+ years of data engineering on AWS
• Hands-on with Glue, Redshift or Snowflake, and Airflow
• Strong data modelling and warehousing skills

Job Summary

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
• Develop automation scripts using Python for data processing and workflow optimization.
• Work with Linux environments for deployment, monitoring, and troubleshooting.
• Ensure data quality, integrity, and reliability across data platforms.
• Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
• Implement best practices for data security, governance, and documentation.

Required Skills

• Strong experience in Data Engineering concepts and ETL/ELT processes.
• Proficiency in SQL, including query optimization and database design.
• Strong programming skills in Python.
• Hands-on experience with Linux commands, shell scripting, and system administration basics.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Familiarity with Git/version control.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
• Experience with data warehousing solutions and big data technologies.
• Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in cloud or data engineering are an added advantage.

Senior Database Administrator (DBA)

Database Reliability & Performance  •  Senior Individual Contributor

• Experience: 6–9 years in production database administration / engineering
• Level: Senior Individual Contributor (hands-on)
• Function: Data Platform — reliability, performance, and governance across relational and distributed SQL & NoSQL DBs.

About the Role

We are hiring a Senior Database Administrator to own the health, performance, and reliability of the data layer behind a high-scale, multi-tenant platform. Our environment spans several independent PostgreSQL database instances, a cache-first read tier, change-data-capture pipeline, analytics and archival stores. Should be capable of implementing NoSQL stores (Cassandra / ScyllaDB) & MySQL  end to end as we scale.

This is a hands-on senior IC role for someone who has run demanding production databases and wants full ownership: partitioning and maintenance, performance tuning, monitoring, uptime, disaster recovery, and the security and data-governance documentation that keeps a regulated, multi-tenant platform audit-ready. You will work closely with, and take direction from, engineering leadership — translating priorities into a well-run, well-documented data platform.

What You'll Own

PostgreSQL Depth

• Administer multiple production PostgreSQL instances (v16+), including schema/DDL review, migrations, and release coordination.
• Design and maintain table partitioning strategies (range/hash/time-based) and automate partition lifecycle — creation, retention windows, and safe drops.
• Own query and instance performance tuning: EXPLAIN/ANALYZE, indexing strategy, autovacuum/bloat management, connection pooling (e.g. PgBouncer), and parameter-group tuning.
• Execute zero-downtime schema changes using expand–migrate–contract / blue-green patterns; assess lock impact and avoid long ACCESS EXCLUSIVE locks on hot tables.
• Manage replica topology (writer/reader endpoints), replication lag, and read-scaling as load grows.
• Partner with app teams on migration tooling (e.g. Flyway) and paired forward/rollback scripts; enforce idempotent, reviewed, tested DDL.

NoSQL & Scale

• Data-model, deploy, and operate distributed NoSQL clusters — Cassandra and/or ScyllaDB — including partition/clustering key design, compaction strategy, repair, and node operations (bootstrap, decommission, scale-out).
• Lead the planned migration of high-volume payload tables from partitioned PostgreSQL to Cassandra/ScyllaDB: capacity planning, dual-write/backfill design, cutover, and validation.
• Tune distributed-store read/write paths, consistency levels, and cluster sizing for predictable latency at scale.
• Support the cache-first architecture (Redis) and change-data-capture / streaming pipelines (e.g. Kafka) that move data to analytics and cold-archival stores.

Operations, Reliability & DR

• Own database uptime and SLOs; build and maintain monitoring, alerting, and dashboards for the key signals (latency, replication lag, CPU/IO, connections, vacuum lag, error rates).
• Define and regularly test backup and disaster-recovery strategy — RPO/RTO targets, point-in-time recovery, restore drills, and cross-AZ / future multi-region readiness.
• Drive incident response for database-related issues: triage, mitigation, root-cause analysis, and follow-up actions.
• Write and maintain runbooks (partition maintenance, failover, archival, DR, migration procedures) and participate in an on-call rotation for the data layer.
• Establish production-change discipline: pre-flight and post-deploy verification, rollback criteria, and backup verification before destructive operations.

Security, Governance & Documentation

• Implement and maintain database access control — least-privilege roles, schema-scoped permissions, and row-level security (RLS) for multi-tenant isolation.
• Own data-governance documentation: PII maps, per-table retention policies, audit-readiness, and the controls behind privacy-regulation compliance (e.g. GDPR / DPDP-style erasure and legal-hold workflows).
• Author and maintain architecture decision records (ADRs), schema documentation, and monitoring/runbook docs so the data platform is legible to the wider team.
• Uphold encryption-at-rest/in-transit posture and safe handling of sensitive columns; keep the data layer aligned with the platform's compliance requirements.

Coding & Automation Bar (Required)

This role is automation-first, not click-ops. The right candidate treats repetitive database work as something to script away and can drop into application code when a problem demands it.

• Strong scripting in Python and Bash for automation of maintenance, backups, partition management, backfills, and health checks.
• Comfortable with infrastructure-as-code (e.g. Terraform) and configuration management (e.g. Ansible) for reproducible database infrastructure.
• Solid SQL and PL/pgSQL; able to read and debug application-layer database code and, worst case, write or patch application code (e.g. Python/Node/Java) to unblock a fix.
• Fluent with Git-based workflows, code review, and CI for database migrations and tooling.

Required Qualifications

• 6–9 years operating relational databases in demanding production environments, with deep PostgreSQL expertise (internals, partitioning, replication, performance tuning).
• Hands-on experience running at least one distributed NoSQL store in production — Cassandra or ScyllaDB strongly preferred (other wide-column/distributed stores considered).
• Proven ownership of backup/DR, monitoring, and incident response for production databases.
• Strong scripting/automation background (Python, Bash) and experience with IaC.
• Experience with managed cloud databases (AWS RDS or equivalent) and understanding of instance/parameter-group tuning, replicas, and failover.
• Experience designing for multi-tenancy and data isolation at scale.
• Clear written communication — able to produce runbooks, ADRs, and governance docs a team can rely on.

Nice to Have

• Experience migrating workloads from PostgreSQL to Cassandra/ScyllaDB (or similar relational-to-distributed migrations).
• Familiarity with Redis as a cache tier and with CDC / streaming pipelines (e.g. Kafka, Debezium).
• Exposure to Flyway (or Liquibase), pgTAP or similar schema testing, and PgBouncer.
• Working knowledge of privacy regulations (GDPR, India DPDP) and audit/compliance processes.

How You Work

• Ownership mindset — takes a directive and runs it to done, with sound judgment on trade-offs.
• Reliability-first and detail-oriented; disciplined about verification, rollback, and documentation.
• Collaborative in a high-performing engineering team; communicates clearly with developers and leadership.
• Pragmatic and scale-aware — designs for where the platform is going, not just where it is.

Job Title: Senior Data Engineer

Position Summary

We are seeking a highly skilled Data Engineer with strong expertise in reporting infrastructure, data modeling, and analytics platforms. This role will focus on building scalable reporting solutions, optimizing data pipelines, and enabling data-driven decision-making across the organization. The ideal candidate will have deep experience with databases, data warehousing, and complex query development. While Ruby on Rails experience is beneficial, the primary emphasis is on data engineering and reporting systems.

Key Responsibilities

• Design, develop, and maintain reporting infrastructure and data platforms.
• Build and optimize complex SQL queries, data models, and reporting datasets.
• Develop scalable ETL/ELT pipelines and data integration processes.
• Design and maintain database schemas to support analytics and reporting requirements.
• Collaborate with business stakeholders to understand reporting needs and translate them into technical solutions.
• Implement data quality, governance, and performance best practices.
• Support and enhance enterprise reporting solutions and dashboards.
• Work with large-scale datasets in cloud data warehouse environments.
• Troubleshoot reporting issues and optimize database performance.
• Partner with engineering and product teams to establish sustainable data architecture.

Must Have: Technical Skills

• PostgreSQL
• Snowflake
• Advanced SQL
• Data Modeling
• Data Warehousing
• Reporting & Analytics Infrastructure
• ETL/ELT Development
• Query Performance Tuning

Success Profile:

The ideal candidate is a data-focused engineer who enjoys working with complex datasets, designing scalable reporting solutions, and building foundational infrastructure that empowers analytics and business intelligence teams. They should be comfortable navigating databases, optimizing queries, and translating business reporting needs into robust technical implementations.

Experience Range: 5-10 years

Role Type: Individual Contributor / Senior Engineer

Primary Focus: Reporting Infrastructure, Data Engineering, Data Warehousing, and Analytics Enablement.

Must-Have Skills

• Minimum 3 years of experience in Data Engineering / Analytics Engineering / Fintech Data roles
• Must have worked on SMS Parsing, intelligent platform, converting RAW customer SMS data into structured actionable financial signals and enabling downstream usage of SMS derived variables
• Must have established a continuous learning cycle to expand parser coverage
• Experience in Lending / NBFC / Fintech domain
• Experience working with Bureau, SMS, Device, or Banking data
• Strong Python and SQL (production level)
• Experience handling unstructured data (SMS, logs, JSON, APIs)
• Experience building data pipelines, schedulers, and cron jobs
• Strong database design and data modelling skills
• Ability to work in a startup environment with high ownership
• Familiarity with modern platforms like AWS, Snowflake, Google BigQuery, Redshift

Good to Have

• Experience in STPL, especially less than 25K ticket size
• Experience with streaming (Kafka/Kinesis) and orchestration (Airflow or Step Functions)
• Experience with feature stores and risk analytics datasets
• Knowledge of regex, NLP basics for SMS parsing
• Experience supporting real-time decision engines/underwriting systems

Role Summary

This role will be responsible for owning the end-to-end data-structuring layer across the organisation. The individual will transform large volumes of raw, unstructured, and semi-structured data (such as SMS, device, bureau, and app data) into clean, standardised, and analysis-ready datasets. These structured datasets will directly power risk analytics, fraud detection, marketing insights, collections strategy, and policy decisioning.

Key Objective of the Role

Ensure all raw lending data (SMS, Bureau, Device, AA, App logs) is captured, parsed, structured, and stored in a clean analytics-ready format inside databases (PostgreSQL, DynamoDB, AWS stack) so that the Risk and Data Science team can directly use it for feature creation, policy building, and portfolio monitoring.

Core Responsibilities

1. End-to-End Data Ownership

• Design, build, and maintain end-to-end data pipelines (batch + streaming) using AWS native services (Glue, Lambda, Step Functions, Kinesis, S3, Athena, Redshift, EMR/Spark, etc.): ingestion

→ parsing → structuring → storage

• Work closely with Tech, Product, and Data Science to define what data should be captured
• Maintain data documentation, data dictionaries, and schema governance
• Ensure data quality, consistency, and version control

1. Unstructured Data Processing (Highest Priority)

• Parse raw SMS dumps and categorise into salary, EMI, loan apps, collections, credits, debits, OTP, etc.
• Process device fingerprint, behavioural logs, and vendor data (FinBox, AA, Bureau APIs)
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• Convert JSON, logs, and raw API responses into structured feature tables
• Build regex/keyword-based parsers for financial SMS classification

1. Feature Implementation (From Risk & Data Science Team)

• Implement feature creation logic provided by Risk/Data Science team
• Translate business and policy logic into SQL/Python pipelines
• Create reusable feature layers for underwriting, fraud, collections, and monitoring
• Maintain a feature store for consistent model and policy usage

1. Lending Data Understanding (Domain-Specific Requirement)

• Work with Bureau data
• Structure SMS-derived financial variables (income, stress, EMI signals)
• Work with Account Aggregator and bank transaction datasets
• Understand fintech alternate data used in underwriting and fraud detection

1. Data Pipelines & Automation

• Build and maintain ETL/ELT pipelines using Python & SQL
• Create cron jobs for automated data ingestion and feature refresh
• Automate vendor data pulls (Bureau, SMS SDK, AA, device data)
• Ensure low-latency pipelines for real-time underwriting use cases

1. Database Structuring & Storage Architecture

• Structure clean datasets in PostgreSQL (analytics layer)
• Manage raw data storage in DynamoDB / S3 data lake
• Design normalized and denormalised tables for risk analytics
• Optimise database performance for large-scale query workloads

1. Dashboards & Readable Data Layer

• Create analytics-ready datasets, implement & write Metabase queries and convert into dashboards (Metabase / Power BI)
• Enable self-serve data access for Risk, Business, and Founders
• Support ad-hoc analysis requirements from leadership

1. Cross-Functional Collaboration (Very Important)

• The role requires close collaboration with data science, tech, product, and business teams to ensure reliable data pipelines, well-defined schemas, API integrations, logging architecture and high data quality, enabling faster and more accurate decision-making across lending workflows.

Tech Stack (Current Environment)

• AWS Services
• PostgreSQL (Primary analytics DB)
• DynamoDB (Raw/NoSQL storage)
• Python (Pandas, NumPy, ETL frameworks)
• Advanced SQL
• APIs, JSON, and Log Data Handling

Overview

Planview has one mission: to build the future of connected work, from ideas to impact.

As the global leader in work and resource management, Planview helps organizations accelerate the achievement of what matters most, supporting our customers from need to speed, from passion to progress, and from overhead to optimization. We provide the industry’s most comprehensive solutions designed for strategic planning, portfolio and resource management, Lean and Agile delivery, product portfolio management, capability, technology management (enterprise architecture), innovation management, collaborative work and project management. Our connected platform of solutions underpins the business and digital transformations of more than 4,500 customers globally, including 59 of the Fortune 100.

At Planview, our people connections drive our innovation and success. Our global team of 1400+ work remotely and across our offices including Austin, Vancouver, Hod HaSharon, Bangalore, and Stockholm. We are proud of our world-class, connected culture built on our shared values, that supports our teams to be successful from anywhere.

The Opportunity

Join our product development team at Planview as a Software Engineer 2 and contribute to the Viz Core Team. This role provides an exciting opportunity to support the development of data processing pipelines and APIs that form the backbone of our software solutions. You will work collaboratively to enhance the efficiency of software delivery, developing solutions that help organizations harness and interpret workflow data.

In this role, you will

•Collaborate with senior engineers to create and refine data processing architectures that integrate with various external tools.

•Assist in analyzing problems, defining requirements, and proposing solutions that align with the team’s objectives.

•Contribute to a culture of quality and continuous improvement by providing thoughtful feedback on code and design.

•Learn and apply best practices in cloud architectures and data processing to deliver high-quality software solutions.

•Engage in an environment that values innovation and teamwork, where your contributions will positively impact the delivery of software solutions.

Who we are looking for

The ideal candidate is an emerging professional in cloud software development with a solid foundation in data processing and software systems. You thrive in collaborative environments and are eager to learn and grow within the field.

Preferred qualifications skills, knowledge, and expertise

•Degree in Computer Science, Engineering, or a related field.

•3+ years of experience with any modern programming language, focusing on back-end systems and cloud-based technologies.

•Basic understanding of data structures, algorithms, and software development methodologies.

•Familiarity with cloud platforms, particularly AWS or similar services.

Other beneficial qualifications

•Exposure to big data technologies like Spark or Apache Kafka.

•Experience with Java (v17), Scala, or other JVM programming languages.

•Familiarity with storage tools such as PostgreSQL and MongoDB.

• Understanding of continuous integration/deployment tooling such as GitHub or Jenkins.

• Awareness of Test-Driven Development practices.

• Basic knowledge of containers and orchestration tools like