Responsibilities
- Understand the values and vision of the organization
- Protect the Intellectual Property
- Adhere to all the policies and procedures
- Design, develop, and maintain scalable data pipelines for data ingestion, processing and storage.
- Build and optimize data architectures and data models (Lakehouse / medallion, dimensional) for efficient data storage and retrieval.
- Develop ETL/ELT processes to transform and load data from various sources into data warehouses and data lakes.
- Build and orchestrate pipelines on Azure Databricks using PySpark, Spark SQL and Delta Lake, orchestrated with Databricks Workflows.
- Integrate data from enterprise source systems including SAP (ABAP/CDS extracts, RPA/CSV or connectors) and load into Snowflake and Databricks.
- Own end-to-end CI/CD for data pipelines using Databricks Asset Bundles (DAB) and Azure DevOps (Git repositories, YAML build and release pipelines), promoting code across dev, QA and production.
- Implement data quality, validation, freshness and reconciliation checks with pipeline observability.
- Ensure data integrity, quality, and security across all data systems.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
- Monitor and troubleshoot data pipelines and workflows to ensure high availability and performance.
- Document data processes, architectures, and data flow diagrams.
Essential Skills
Job
- 7 - 8 years of hands-on data engineering experience building and running production data pipelines at scale.
- Strong expertise in Azure and Azure data services (ADLS Gen2, Azure Databricks, Azure DevOps).
- Deep hands-on experience with Databricks: PySpark, Spark SQL, Delta Lake, Lakehouse / medallion architecture and Databricks Workflows.
- CI/CD for data engineering using Databricks Asset Bundles (DAB) and Azure DevOps (Git, YAML build/release pipelines, multi-environment promotion). (Must-have)
- Strong Snowflake experience (data modeling, performance tuning, loading and optimization).
- Proficiency in SQL and Python.
- Experience integrating data from SAP and other enterprise ERP / source systems into a data lake or warehouse.
- Solid data modeling (dimensional, star/snowflake, Lakehouse) and ETL/ELT design.
- Building data-quality, validation, reconciliation and pipeline monitoring / observability.
Personal
- Excellent communication and interpersonal skills, with the ability to engage with all levels of employees and management.
- Collaborative approach to effectively present and advocate for quick design solutions.
- Stay updated on the latest design trends, tools, and technologies, bringing innovative ideas to enhance the product experience.
- A proactive approach to problem solving, with a focus on delivering exceptional customer satisfaction.
Certifications
- At least one current certification is required; multiple is a strong plus:
- Databricks Certified Data Engineer Associate or Professional. (Required)
- Microsoft Certified: Azure Data Engineer Associate (DP-203), or Azure Fundamentals (DP-900 / AZ-900).
- SnowPro Core or SnowPro Advanced: Data Engineer (Snowflake).
Preferred Skills
Job
- Familiarity with SAP finance / ERP data domains (Accounts Receivable, invoice-to-pay, bank statements).
- Streaming and event-driven pipelines (Apache Kafka / Azure Event Hubs).
- Workflow orchestration (Apache Airflow, Databricks Workflows).
- Databricks Unity Catalog and Delta Live Tables.
- Infrastructure as Code (Terraform) and containerization (Docker).
- Data governance, lineage and cost/performance optimization on Databricks and Snowflake.
- Exposure to BI / visualization tools (Power BI, Tableau).
Personal
- Demonstrate proactive thinking
- Strong communication and collaboration skills.
- Should have strong interpersonal relations, expert business acumen and mentoring skills
- Strong problem-solving skills with attention to detail.
- Have the ability to work under stringent deadlines and demanding client conditions.
- Strong analytical and problem-solving skills.
- Ability to work independently and as part of a team.
Other Relevant Information
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- 7 - 8 years of experience in data engineering & architecture, including hands-on Databricks and Azure DevOps CI/CD.
- This role offers the flexibility of working remotely in India.
LeewayHertz is an equal opportunity employer and does not discriminate based on race, color, religion, sex, age, disability, national origin, sexual orientation, gender identity, or any other protected status. We encourage a diverse range of applicants.
Skills Required
- 7–8 years of hands-on data engineering experience building and operating production data pipelines at scale
- Strong expertise in Azure data services, including ADLS Gen2, Azure Databricks, and Azure DevOps
- Hands-on Databricks experience with PySpark, Spark SQL, Delta Lake, Lakehouse or medallion architecture, and Databricks Workflows
- CI/CD experience using Databricks Asset Bundles and Azure DevOps, including Git, YAML pipelines, and multi-environment promotion
- Strong Snowflake experience in data modeling, performance tuning, loading, and optimization
- Proficiency in SQL and Python
- Experience integrating SAP and other enterprise ERP or source systems into data lakes or warehouses
- Experience with dimensional, star or snowflake, and Lakehouse data modeling and ETL/ELT design
- Experience building data-quality, validation, reconciliation, monitoring, and observability solutions
- At least one current certification, including Databricks Certified Data Engineer Associate or Professional
- Bachelor’s degree in Computer Science, Information Technology, or a related field
- Familiarity with SAP finance or ERP data domains
- Experience with Apache Kafka or Azure Event Hubs
- Experience with Apache Airflow or Databricks Workflows
- Experience with Databricks Unity Catalog or Delta Live Tables
- Experience with Terraform and Docker
- Experience with Power BI or Tableau
- Azure Data Engineer, Azure Fundamentals, or Snowflake certification
The Hackett Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Hackett Group and has not been reviewed or approved by The Hackett Group.
-
Flexible Benefits — Remote/hybrid flexibility is consistently highlighted, with support for home-office expenses in some cases. Feedback suggests location flexibility is a bright spot that improves day-to-day experience.
-
Fair & Transparent Compensation — Publicly posted salary ranges and role-specific target bands offer clear expectations and help candidates assess fit. Feedback suggests compensation can be competitive for certain roles and markets.
The Hackett Group Insights
What We Do
The Hackett Group, Inc. (NASDAQ: HCKT) is a Gen AI strategic consulting and executive advisory firm that enables Digital World Class® performance. Using Hackett AI XPLR™ and ZBrain™ – our ideation through implementation platforms – our experienced professionals help organizations realize the power of Gen AI and achieve quantifiable, breakthrough results, allowing us to be key architects of their Gen AI journey. Our expertise is grounded in unparalleled best practices insights from benchmarking the world’s leading businesses – including 97% of the Dow Jones Industrials, 89% of the Fortune 100, 70% of the DAX 40 and 55% of the FTSE 100. Visit us at www.thehackettgroup.com.








