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Technical Lead – Data Engineering

EvoluteIQ
Bengaluru, Karnataka

Apply Now

Job details

Permanent

Qualifications

CI/CD
Azure
Big data
Software deployment
Spark
Encryption
NoSQL
Java
SQL
AWS
Scala
Continuous integration
SDKs
APIs
Kafka
Metadata
Communication skills
Graph databases
Python

Full job description

Job Type:

Permanent

Experience:

10+ Years

Location:

Bangalore

Life at EvoluteIQ

We at EvoluteIQ believe in the power of transformation. We are committed to building a industry-leading technology that will revolutionize the way enterprises conduct business.

To make that happen, we need people who are generous, genuine, self-driven and collaborative. People who not only want to be a part of a fast-growing and radical thinking company, but who are kind and care—about each other. We at EvoluteIQ thrive in the company of each other and make each other a better version of ourselves every day.

Could that be you?

The EIQ Mission:

Our culture is who we are, and it defines us. We are nimble, fast, dedicated, humble and bold. We see opportunities everywhere around us to make a “dent in the universe”. Our core fabric is Innovation! And this is not just a word, but the way of life within EvoluteIQ.

Changing the way business is done, reimagining the future of work, and enabling people to improve their quality of work every day, is a daunting task. That is what we all strive every day at EvoluteIQ. To enable everyone to automate complicated processes with their instinct and knowledge.

We make building of automation simple for everyone, so that it is not mystery for a few.

Would you like to be part of this journey?

About the role

We are building EIQ, a platform product that enterprises use, among other things, to make their data governed, secured, controlled, discoverable, curated, processed, and delivered — across every stage of the data lifecycle. We don’t just move data, we operationalize the full Variety Velocity Volume Value chain while keeping Visibility and Veracity intact and Vulnerability minimized.

This is a product engineering role, not a solutions role. You will not be building pipelines for a single business. You will be building the platform on which thousands of pipelines, models, and data products are designed, deployed, monitored, and trusted. The distinction matters: every component you build is a capability shipped to customers, not a one-off integration. Reusability, configurability, multi-tenancy, observability, and extensibility are first-class concerns in everything you write.

What you'll do at EvoluteIQ:

You will lead engineering on one or more areas of the EIQ data processing stack:

Data Producer and Ingestion layer: Connectors and ingestion engines spanning batch, mini-batch, real-time streaming, CDC, pub-sub, queues, and ESB integrations across SQL/NoSQL sources, SaaS apps, IoT/edge, clickstreams, and event/webhook streams. Structured, semi-structured, and unstructured. Cloud and on-premise.
Data Processing engine: Wrangling, transformation, ETL/ELT, stream processing, microbatching, enrichment, compaction, and workflow orchestration as configurable platform capabilities.
Data Storage abstraction: A unified interface across data lakes, warehouses, lakehouses, object stores, graph DBs, and row/columnar stores with schema management, compression, and caching built in.
ML enablement: The substrate on which feature engineering, model training, evaluation, tuning, refinement, and MLOps run as productized workflows.
Cross-cutting platform capabilities: Metadata management (registry, cataloguing, lineage, tagging, version control), data quality and integrity (accuracy, freshness, deduplication, lifecycle, MDM, testing), and data security (authN/authZ, encryption at rest and in transit, policies, compliance, observability, auditing, alerting).

Key Responsibilities:

Lead technical execution for one or more pillars of the EIQ platform: Translating the platform’s architectural direction into concrete designs for storage abstractions, processing engines, connector frameworks, and metadata models that scale to enterprise customers across industries.
Build for multi-tenancy, extensibility, and configurability: Every feature should generalize across customer workloads, not solve one use case.
Lead a team of data and platform engineers as their technical anchor. Set the technical bar, run design reviews, unblock the team, and mentor on tradeoffs between performance, cost, reliability, and developer experience.
Drive component-level build-vs-buy-vs-integrate decisions within the platform’s architectural direction. Know when to leverage Spark/Kafka/Airflow/dbt/Iceberg/Delta and when to build proprietary capability that differentiates the product.
Productize governance, security, and observability as platform-native features — not bolt-ons. The components your team ships must be auditable, lineage-aware, and policy-enforcing by default.
Partner closely with the architect, Product Management, Data Science, and Design to translate customer-facing capabilities into engineering plans your team can execute against. Bring engineering reality into architectural discussions; bring architectural intent into your team’s day-to-day.
Understand the persona using each feature — data engineer, analyst, scientist, steward, security officer — and make sure that’s reflected in how the team designs APIs, SDKs, and UX.
Establish engineering excellence — CI/CD, automated testing across unit/integration/contract layers, release packaging, performance benchmarking, SLO-driven observability, and incident response.
Be a technical voice in competitive positioning. Understand what competitors do well, where they fall short, and where EIQ wins.

What will you bring to the team?

10+ years in data engineering, with at least 2–3 years as a tech lead or senior engineer guiding a team. Bonus if some of that time was building a product shipped to external customers rather than internal pipelines.
Deep expertise in SQL, Python (Scala or Java a plus), and the modern big data ecosystem — Spark, Kafka, Airflow, Flink, dbt, Iceberg/Delta/Hudi.
Hands-on with at least one major cloud (AWS, Azure, or GCP) and ideally experience designing for cloud-agnostic or hybrid deployment.
Strong grasp of data modeling, warehousing, lakehouse architecture, and real-time/streaming processing — and the tradeoffs between them.
Platform thinking. You’ve designed systems with APIs, SDKs, plugin architectures, multi-tenancy, or self-service workflows — not just DAGs that move data from A to B.
Governance and security as instinct. You understand lineage, cataloguing, access controls, encryption, and compliance frameworks (GDPR, HIPAA, SOC 2) as engineering requirements, not afterthoughts.
Proven technical leadership — running design reviews, growing engineers, driving delivery across complex, ambiguous projects, and earning trust as the senior engineer in the room.
Excellent communication. You can explain a partitioning strategy to a junior engineer and a roadmap tradeoff to an architect or PM in the same afternoon.

Good To Have:

Experience building or contributing to a data platform product (Fivetran, Hevo, Airbyte, Databricks, Snowflake, Confluent, Estuary, Matillion, or similar).
Familiarity with metadata and catalog tools (DataHub, Amundsen, OpenMetadata, Collibra, Alation).
Background in MLOps platforms or feature stores.
Open-source contributions to the modern data stack.

What Sets This Role Apart:

Most “lead data engineer” roles are about wiring data flows inside one company. This one is about leading engineering on the product that other companies’ data engineers will use to wire their flows — at scale, under governance, with security and lineage baked in. You won’t own the platform architecture, but you will own how a meaningful part of that platform actually gets built, shipped, and made trustworthy in production. If that distinction excites you, we should talk.

What We Offer:

Opportunity to shape the strategy of a next-gen hyper-automation platform.
Work with a cross-disciplinary team in a fast-growing, innovation-driven environment.
Competitive compensation and growth opportunities.
A culture of innovation, ownership, and continuous learning.

Ready to take the next step in your career journey with us? Apply now and become part of a dynamic team that values expertise, collaboration, and a positive work culture!

Don’t Meet Every Requirement? We Still Want to Hear From You!

Please go ahead and apply anyway.

We know that experience comes in all shapes and sizes and passion can’t be learned. If you believe, then we would like to meet you and explore that belief!

We value a range of diverse backgrounds, experiences, and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, colour, religion, sex, sexual orientation, gender identity and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes.

Apply Now

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