Tech Lead - Data Engineering

Position: Technical Architect – Data Engineering

Job Summary:

• We are looking for an experienced Technical Architect to lead the design and implementation of modern cloud-based data platforms.
• The ideal candidate should have strong expertise in Azure and/or AWS, Databricks, Snowflake, modern data architecture, and large-scale data engineering.
• The candidate will work closely with business stakeholders, architects, and engineering teams to deliver scalable, secure, and high-performance data solutions.

Key Responsibilities

• Design enterprise-scale data lakehouse and data warehouse architectures.

• Define data ingestion, transformation, and serving architecture.

• Lead architecture discussions and technical governance.

• Design scalable ETL/ELT frameworks using Databricks and Snowflake.

• Define best practices for security, performance, CI/CD, and DevOps.

• Guide engineering teams on implementation.

• Collaborate with business, product, and data governance teams.

Must Have Skills :

• Azure or AWS

• Databricks

• Snowflake

• Data Lakehouse Architecture

• PySpark

• SQL

• Data Modelling

• ETL/ELT Architecture

• Performance Optimization

• CI/CD

• Terraform or Infrastructure as Code (preferred)

Preferred

• Insurance domain

• dbt

• Unity Catalog

• Delta Lake

• Iceberg

• Azure Data Factory / AWS Glue  

Job Overview:

We are seeking an experienced Cloud Data Engineer to the architecture, development, Data migration, ETL pipeline in cloud and optimization of a next-generation data platform. This is a development role for an individual with over 4 years of deep data engineering and data migration, data pipeline in AWS expertise, capable of driving technical direction, and delivering high-impact solutions in a fast-paced

4+ Years of hands-on, progressive experience in Cloud Data Engineering, cloud ecosystems AWS, Data Architecture

• Deep conceptual understanding of core data engineering principles, ETL/ELT patterns, and metadata management

•  Ability to translate complex business needs into actionable technical requirements.

•  Strong troubleshooting and problem-solving skills in distributed systems.

•  Agile/Scrum teamwork capabilities and version control practices

• Insurance industry experience preferred but not mandatory

• Tools:

o Cloud Environment: AWS (S3, IAM, VPC, Glue, Lambda etc.)

o Experience with dbt Core, Iceberg, AWS Glue Catalog, AWS lambda, Redshift, Athena, Splunk, AmazonQ, AWS streaming services, Git

o Strong SQL, Pyspark and Python

Key Skills:

Python & System Design: Strong expertise in Python and system design, with proven experience architecting scalable, production-grade systems.

LLM & Agentic AI: Proven experience building LLM-based and agentic systems from the ground up and evaluating them based on reproducibility, calibration, and cost.

Cloud & Data Architecture: Deep understanding of data and cloud architecture across AWS and Azure, including multi-store data design, distributed systems, streaming, security, and cost optimization.

Azure Databricks: Hands-on production experience with Azure Databricks architecture, including Unity Catalog, Delta Lake, cluster policy design, job orchestration, and Terraform provisioning.

Supply Chain & Inventory Management: Strong domain knowledge of supply chain and inventory operations, including demand planning, MRP logic, inventory parameters, and translating business planning decisions into data requirements.

System Architecture & Technical Decision-Making: Ability to make sound architectural decisions based on first principles, evaluate technical trade-offs, and avoid unnecessary complexity and abstraction.

LLM & Agentic AI: Proven experience building LLM-based and agentic systems from the ground up and evaluating them based on reproducibility, calibration, and cost.

Technical Leadership: Ability to influence teams without direct authority, establish technical standards, prepare technical specifications and documentation, and mentor team members.

Experience in pharmaceutical or regulated industries is highly valued.

Job Title: Senior Data Architect

Experience: 7+ Years

Location: India (Ahmedabad / Hybrid/Remote)

Job Summary

We are looking for an experienced Senior Data Architect to support the modernization and enhancement of Enterprise Analytic Data Warehouse (ADW). The candidate will be responsible for evaluating existing data architecture, designing scalable data models, assessing data integration across clinical, operational and financial domains, and establishing data governance and data quality standards.

Key Responsibilities

• Assess and review the existing Enterprise Analytic Data Warehouse architecture, database structures and data integration processes.
• Design and improve enterprise data models covering clinical, operational, financial and revenue-cycle information.
• Define data architecture standards, database structures, data relationships and integration strategies.
• Evaluate data flows between source systems and the data warehouse.
• Design and review source-to-target mappings and data lineage.
• Identify architectural gaps affecting data completeness, consistency, integrity and reporting accuracy.
• Establish standardized data definitions, data governance practices and metadata management.
• Ensure consistent patient, facility, payer and other critical identifiers across different datasets.
• Support integration of billing, claims, payment, denial and accounts receivable (AR) data.
• Work with SQL and Python-based data processing solutions to investigate and validate data structures.
• Recommend improvements to warehouse scalability, performance, reliability and maintainability.
• Develop a prioritized architecture and modernization roadmap for future implementation.
• Coordinate with data engineers, analytics engineers and business stakeholders.

Required Technical Skills

• Strong experience in Data Architecture and Enterprise Data Warehousing.
• Advanced SQL and relational database concepts.
• Experience with data modelling (conceptual, logical and physical).
• Knowledge of ETL/ELT pipelines and data integration.
• Experience with data profiling, data lineage and metadata management.
• Understanding of data governance, data quality and data validation frameworks.
• Experience working with large and complex datasets.
• Python knowledge for data analysis and validation.
• Experience with cloud-based data platforms or modern data warehouse technologies.

Preferred Skills

• Experience with Databricks, Azure, AWS or similar cloud data platforms.
• Experience with healthcare data warehouses.
• Knowledge of clinical, financial, billing and claims datasets.
• Understanding of HIPAA, PHI and healthcare data security principles.
• Experience with healthcare analytics, reimbursement and revenue-cycle data.

Strong Data Analyst Profile with Python, SQL, and data-pipeline expertise, ideally with retail / e-commerce datasets

2

Mandatory (Experience 1): Must have 4+ years of hands-on data-analyst experience, working with large datasets across areas such as sales, inventory, pricing, promotions, and customer behaviour.

3

Mandatory (Tech skill 1): Must have strong hands-on Python for data processing, transformation, automation, and analysis

4

Mandatory (Tech skill 2): Must have strong SQL skills, including complex queries, joins, aggregations, and data validation.

5

Mandatory (Tech skill 3): Must have a solid understanding of Data Lake architecture, ingestion, storage, and processing workflows

6

Mandatory (Tech skill 4): Must have hands-on experience with ETL / ELT pipelines, data integration, and transformation

7

Mandatory (Tech skill 5): Must have experience with Azure or GCP data services.

8

Mandatory (Tech skill 6): Must have understanding of or experience with Databricks and distributed data processing.

9

Mandatory (Tech skill 7): Must have knowledge of data modeling, data warehousing, and Lakehouse architecture

10

Mandatory (Tech skill 8): Must have experience with Power BI, Tableau, or Excel for reporting.

11

Mandatory (Communication): Must have strong analytical, documentation, and stakeholder-communication skills.

12

Mandatory (Education): Must hold a Bachelor’s degree in Computer Science, IT, Engineering, or a related field.

13

Mandatory (Note1): This is a 6-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

As a Solutions Engineer/Sales Engineer, you will act as a trusted technical advisor to prospective customers in the US market. You will own the technical evaluation journey end-to-end, from the first discovery call to closing the deal, by demonstrating how our platform solves real-world data integration challenges. This role involves working closely with global customers (primarily North America ), designing scalable architectures, running tailored product demos, and building proofs-of-concept that showcase value.

Responsibilities:

• Run technical discovery calls with Heads of Data, Data Engineering Managers, and CTOs to understand their stack, pain points, and constraints. These are global conversations, primarily with customers in North America and Europe, and you will own them end-to-end.
• Design and present reference architectures showing how Hevo fits into their existing data stack (e. g., Salesforce, Postgres, GA4 Snowflake, dbt).
• Run live product demos tailored to the customer's stack. These are not scripted walkthroughs. You will need to read the room, adapt on the fly, and handle unexpected technical questions with confidence.
• Own the technical evaluation from the first conversation to the closed deal by addressing deep technical questions and earning trust with engineering teams.
• Build proofs-of-concept by configuring real pipelines from source systems (Salesforce, Outreach, Postgres, MySQL) into destinations like Snowflake or BigQuery.
• Develop deep expertise in the data integration landscape, including native solutions from AWS, GCP, and Azure (AWS Glue, Azure Data Factory, Google Cloud Dataflow) as well as other data pipeline and integration platforms, and articulate Hevo's technical advantages in a way that lands with both technical and non-technical buyers.
• Partner with Account Executives to drive technical wins and with Customer Success to ensure smooth handoffs after a deal closes.
• Share customer feedback and patterns with Product and Engineering to influence the roadmap.

Requirements:

• 2 to 6 years of hands-on experience as a Data engineer, Analytics engineer, ETL/ELT developer, or Data warehouse engineer.
• Experience building and operating real data pipelines in production, including handling source schema changes, failures, and reliability issues.
• Strong fundamentals in SQL and at least one cloud data warehouse (Snowflake, BigQuery, or Redshift).
• Experience with at least one orchestration or transformation tool (Airflow, dbt, or similar).
• Exceptional communication and presentation skills.
• This is non-negotiable. You will be the face of Hevo's technical capability to a global customer base. That means:
• Your spoken English is clear, confident, and easy to follow for an international audience.
• You are comfortable presenting to groups of 5 to 15 people, including senior technical leaders, over video calls.
• You can structure a technical narrative, not just answer questions but guide a conversation toward the right conclusion.
• You can hold your own when a customer pushes back or challenges your recommendation.
• You have presented or demoed something technical to an audience before, in any context: internal reviews, client calls, meetups, or conferences.
• Genuine interest in customer-facing work, even if you have not done it formally before.

Good to have:

• Experience with CDC tools or data integration platforms, whether cloud-native (AWS Glue, Azure Data Factory, or Google Cloud Dataflow) or third-party pipeline and integration tools.
• Exposure to multiple source system types such as CRMs, ad platforms, SaaS APIs, and OLTP databases.
• Public technical writing, conference talks, or open-source contributions.
• Prior experience in customer conversations, even informally. For example, presenting to internal stakeholders or analytics teams or working with international teams across time zones.

Job Summary

We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.

Technical Skills

• Strong hands-on experience in Python and PySpark development.
• Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
• Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
• Experience with Power BI Data Modeling and Semantic Layer development.
• Proficiency in DAX (Data Analysis Expressions).
• Experience designing and managing Semantic Models in Power BI.
• Strong SQL skills and experience working with large datasets.
• Knowledge of data warehousing concepts and best practices.

Preferred Skills

• Experience with cloud platforms such as Azure, AWS, or GCP.
• Exposure to modern data platforms like Databricks.
• Understanding of data governance and data quality frameworks.

Immediate Joining

We are looking for a Dedicated Resource on Contract for –

Role: Data Engineer

Experience: 5+ Years

Location: Remote

Duration: 3+ Months

Strong hands-on experience with Snowflake, including writing SQL queries, creating views, stored procedures, and functions.

Good knowledge of AI tools such as Claude.

Experience with ETL tools like Alteryx is good to have.

Power BI experience is good to have.

Strong communication skills.