Tech Lead - Data Engineering

Job Summary

The Technical Lead will be responsible for overseeing and leading projects related to Azure Data Factory (ADF), Azure Databricks, SQL, Oracle PL/SQL, and Python. The role involves designing, developing, and implementing data solutions while ensuring they meet the business requirements and align with best practices. (1.) Key Responsibilities

1. Lead and manage end-to-end data engineering projects using azure data factory, azure databricks, sql, oracle pl/sql, and python.

2. Collaborate with stakeholders to gather and understand requirements for data pipelines and analytics solutions.

3. Design and develop etl processes, data models, and data integration solutions.

4. Provide technical guidance and mentorship to the team members.

5. Ensure data quality, data governance, and data security standards are maintained throughout the project lifecycle.

6. Troubleshoot and optimize data pipelines and processes for performance and efficiency.

7. Stay updated on the latest trends and technologies in data engineering and contribute to continuous improvement efforts.

Skill Requirements

1. Proficiency in azure data factory (adf) and azure databricks for building and managing data pipelines.

2. Strong experience with sql and oracle pl/sql for data querying and manipulation.

3. Advanced programming skills in python for scripting and data processing tasks.

4. Knowledge of data modeling, data warehousing concepts, and database design principles.

5. Ability to work in a collaborative team environment and communicate effectively with stakeholders.

6. Strong analytical and problem-solving skills with attention to detail.

7. Experience in data visualization tools and techniques is a plus.

Certifications: Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle PL/SQL, or Python are advantageous.

Skill (Primary)

Data Fabric-Azure-Azure Data Factory (ADF)

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  

Location: Hyderabad / Chennai

Experience: 5+ years

Employment type: Full-time, permanent

Work Hours: General Shift

website: www.amazech.com

Qualifications: 

• B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
• Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.

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.

Solution Architect – AZURE Data Engineering

Job Overview

We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.

Key Responsibilities

• Design and implement scalable data architecture and solutions.
• Develop and manage Data Warehouse and Data Lake architectures.
• Design data platforms using Medallion Architecture.
• Lead Data Engineering and ETL activities.
• Work with Azure Synapse Analytics for data processing and analytics.
• Develop data solutions using PySpark / Apache Spark.
• Define and implement data validation and data quality processes.
• Collaborate with business, data, and technology teams to deliver effective data solutions.

Required Skills

• Strong experience in Solution Architecture / Data Architecture.
• Strong knowledge of Data Warehouse and Data Lake architecture.
• Good understanding of Medallion Architecture.
• Strong experience in Data Engineering and ETL.
• Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
• Strong knowledge of PySpark / Apache Spark.
• Experience with Data Validation and Data Quality.
• Good communication and stakeholder management skills.
• 
  

Experience

8+ Years

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.