Data Delivery Manager

Key Responsibilities

• Lead end-to-end data migration initiatives, including assessment, planning, mapping, transformation, validation, and reconciliation.
• Define and implement data governance frameworks, standards, policies, and processes.
• Design and manage data solutions using Microsoft Azure Data Services.
• Lead development of BI dashboards, reports, KPIs, and analytics solutions.
• Work with business and technical stakeholders to understand reporting and data requirements.
• Develop and maintain data models, data pipelines, ETL/ELT processes, and reporting architecture.
• Ensure data quality, consistency, integrity, security, and compliance throughout migration and reporting processes.
• Identify data risks, dependencies, gaps, and migration challenges and drive their resolution.
• Establish data validation and reconciliation mechanisms to ensure migration accuracy.
• Provide technical leadership and guidance to data engineers, BI developers, and other project team members.
• Collaborate with application, cloud, infrastructure, and business teams during project implementation.
• Monitor data migration and BI deliverables against project timelines, quality standards, and business objectives.
• Prepare technical documentation, data dictionaries, mapping documents, governance guidelines, and project reports.

Required Skills & Experience

• 7+ years of experience in data, migration, BI, or related technology roles.
• Strong experience working on software/IT projects and managing data-related workstreams.
• Hands-on experience with Microsoft Azure Data Services.
• Strong understanding of data migration methodologies, ETL/ELT, data transformation, and reconciliation.
• Experience in Data Governance, Data Quality, Master Data, Metadata Management, and Data Security.
• Strong experience with BI reporting and dashboard development.
• Good understanding of SQL and relational databases.
• Experience with Power BI and data visualization is highly desirable.
• Knowledge of Azure services such as Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure SQL Database, or equivalent.
• Strong understanding of data architecture and data lifecycle management.
• Excellent stakeholder management, communication, analytical, and problem-solving skills.

Hiring for Data Engineer - Delivery Manager

Exp : 10 - 15 yrs

Edu : BE/B.Tech/MCA

Work Loation : Hyderabad

.Roles & Responsibilitie:

Own end-to-end delivery of data engineering programs ensuring alignment with business goals, timelines, and quality standards.

Drive execution across multiple data initiatives within Azure and Databricks environments.

Provide technical leadership in designing and implementing scalable data pipelines using Python, PySpark, and Spark.

Required Skills:

Strong experience with Databricks, PySpark, Python, and Spark.

Expertise in Azure Data Services including ADF, ADLS, and Synapse.

Proven experience in delivery management, stakeholder management, and Agile execution

15+ years of IT Delivery and Technology Services experience.

15+ years managing large offshore delivery organizations.

Proven leadership of portfolios exceeding 200+ resources.

Financial Services or Banking experience is a MUST

Extensive technical experience in Data Engineering, Data Platforms, Data Brics.

Cloud Data Transformation Programs, Data Warehousing, Azure Data Platform and compliance experience

At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available.

For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.

As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work!

Job Overview 

Principal Data Engineer

About Engineering at Mitratech Legal Solutions 

Mitratech's engineering organization is a collaborative and dynamic environment where engineers are empowered to drive technical direction and innovation. Our engineers are passionate about delivering high-quality products and solutions that meet the evolving needs of our customers, and we're committed to fostering a culture of continuous learning and growth. 

About the Role 

Mitratech is a fast-paced and dynamic environment, and this role requires someone who is adaptable, resilient, and able to thrive in a rapidly changing landscape. If you’re a seasoned engineer with a passion for technical leadership, innovation, and collaboration — including building the data foundations that power trusted reporting and agentic AI-driven products — we’d love to hear from you. 

What You Will Do

•  Drive technical direction for a significant product domain or platform capability, ensuring alignment with business objectives and customer needs 

•  Design and maintain data pipelines and reporting models that power trusted business metrics and increasingly feed agentic AI systems (e.g., RAG ingestion, embeddings, vector stores, AI agent workflows) 

•  Use AI-assisted and agentic engineering tools (e.g., Claude Code, Copilot, Cursor, AI agents) as part of your own workflow, and help other engineers adopt agentic development practices effectively 

•  Reduce systemic complexity by identifying and leading architectural debt remediation, and developing strategies for ongoing technical debt management 

•  Partner with Product and Engineering leadership to inform multi-quarter roadmap feasibility, and provide technical guidance and oversight to ensure successful implementation 

•  Elevate engineering craft across multiple teams through RFCs, mentorship, and knowledge sharing, and develop training programs to improve engineering skills and knowledge 

•  Represent Mitratech’s technical capabilities externally, including speaking at conferences, contributing to open-source projects, and engaging with industry peers and thought leaders 

What We Are Looking For 

To be successful in this role, you will need: 

•  10+ years of experience in software engineering, with a focus on technical leadership and architecture 

•  Deep understanding of data engineering principles, including data modeling, data warehousing, reporting, and data governance 

•  Strong technical expertise in SQL, PostgreSQL, ETL/ELT pipelines, BI tools, and analytics platforms 

•  Practical experience with AI/LLM-adjacent and agentic AI data work — e.g., RAG ingestion pipelines, embedding generation, vector store management, or building/operating AI agent workflows over data — using AI coding assistants (Claude Code, Copilot, Cursor, or similar) as a regular part of the engineering workflow 

•  Working knowledge of modern cloud platforms such as AWS 

•  Experience with BI, reporting, dashboards, and customer-facing analytics 

•  Experience leading cross-functional initiatives with product, engineering, analytics, and business teams 

Nice to Have 

•  Working knowledge of Ruby on Rails and React 

•  Experience with a semantic or metrics layer (e.g., dbt Semantic Layer, headless BI) 

•  Understanding of CI/CD, Git-based workflows, and infrastructure-as-code 

The Stack Context 

•  Modern data stack: Fivetran, Airbyte, dbt, Snowflake, GitHub, Terraform, or similar tools 

•  Application context (nice to have): Ruby on Rails, React, or similar backend/frontend frameworks 

•  Data modeling: SQL, analytics models, documentation, testing, naming standards, and version control 

•  Infrastructure: cloud-based data infrastructure, infrastructure-as-code, CI/CD, monitoring, and cloud storage 

•  Data workflows: ingestion, transformation, orchestration, reporting, deployment, and change management 

•  Reporting focus: trusted metrics, scalable reporting models, dashboards, exports, and data quality 

•  AI surface: data pipelines and quality practices supporting AI/LLM and agentic AI use cases (RAG, embeddings, vector stores, AI agents) alongside traditional BI 

Why This Role 

This role offers a unique opportunity to drive technical direction and innovation at a rapidly growing company, while also mentoring and coaching engineers to improve their craft. As a Principal Data Engineer at Mitratech, you will have the chance to work on complex and challenging problems spanning trusted reporting and agentic AI systems, collaborate with cross-functional teams, and represent the company's technical capabilities externally. If you're looking for a role that offers a mix of technical leadership, data and reporting depth, agentic AI innovation, and collaboration, this could be the perfect fit for you. 

We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.

Job Summary

Role Overview

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.

Experience with Google Cloud Platform (GCP) will be an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Develop complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain reliable data integration workflows across multiple data sources.
• Perform data cleansing, validation, transformation, and quality checks.
• Analyze data and provide insights to support business and technical requirements.
• Implement and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
• Troubleshoot data pipeline failures, performance issues, and production incidents.
• Optimize data processing workflows for performance, scalability, and reliability.
• Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
• Follow best practices for version control, testing, documentation, and deployment.
• Contribute to cloud-based data engineering initiatives, preferably on GCP.

Required Skills

• 5–7 years of hands-on experience in Data Engineering.
• Strong programming skills in Python.
• Strong expertise in Advanced SQL and database concepts.
• Hands-on experience with ETL/ELT processes and data pipelines.
• Good understanding of Data Warehousing and Data Modeling concepts.
• Experience with CI/CD practices and tools.
• Strong understanding of DevOps principles, automation, and deployment processes.
• Strong data analytics and problem-solving skills.
• Experience working with large datasets and performance optimization.
• Good understanding of Git/version control and software development best practices.

Good to Have

• Hands-on experience with Google Cloud Platform (GCP).
• Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
• Experience with containerization/orchestration technologies such as Docker/Kubernetes.
• Experience with workflow orchestration tools such as Airflow.
• Knowledge of cloud-based data architecture and distributed data processing.

Preferred Candidate Profile

• Strong analytical and problem-solving abilities.
• Good communication and stakeholder management skills.
• Ability to work independently as well as in a collaborative team environment.
• Strong ownership of data pipelines and production systems.
• Candidates who can join at short notice are preferred.

Mandatory Skills

 Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops

Example:

We are looking for an experienced Data Architect to design, develop, and manage the organization's enterprise data architecture. The candidate will be responsible for building scalable data platforms, ensuring data quality and governance, and supporting business analytics through modern data solutions.

Experience Required

Mention the minimum years of experience.

Example:

• Minimum 12 years of experience in Data Architecture, Data Engineering, or related fields.
• 5+ years of experience in the Banking/Financial Services domain is preferred.

Educational Qualification

Mention the required degree.

Example:

• BE/BTech in Computer Science, Information Technology, Software Engineering, Electronics & Communication Engineering, or equivalent.
• OR MCA/MTech/MSc in Computer Science, IT, or related disciplines.
• MBA is preferred.

Technical Skills

List the skills the candidate must have.

Example:

• AWS, Azure, or GCP
• Data Warehousing (DWH)
• ETL/ELT
• Database Management
• Data Modeling
• Data Analytics
• Data Lakes
• Data Governance

Key Responsibilities

Convert the points you received into simple action statements.

Example:

• Design and maintain enterprise data architecture.
• Develop data warehouses and data lakes.
• Define data standards and governance policies.
• Ensure data quality and security.
• Design ETL/ELT processes.
• Integrate data from multiple systems.
• Plan and execute data migration projects.
• Review existing data architecture and recommend improvements.
• Provide technical guidance to project teams.
• Evaluate new data technologies and tools.

Preferred Skills

These are not mandatory but are an advantage.

Example:

• Banking domain experience
• Strong analytical and problem-solving skills
• Good communication skills
• Leadership and stakeholder management
• Experience mentoring technical teams

About AuxoAI:

AuxoAI is a global platform-based services firm. We help companies—turn their strategies into practical digital and AI solutions. By understanding how our clients make decisions, we use digital and Artificial Intelligence (AI) technologies to drive growth, enhance their operations, improve customer experiences, and provide clear, actionable insights from their data. What We Do We work across various industries such as healthcare, high-tech, consumer packaged goods (CPG), finance etc., and in sales, marketing, and customer support functions.

We help our clients with accelerating their digital and AI journeys through:

• AI Application Development

• Data, Digital and Cloud acceleration using AI

• AI Native Product Engineering

We are seeking a skilled and experienced Data Engineer to join our dynamic team. The ideal candidate will have 6+ years of prior experience in data engineering, with a strong background in AWS (Amazon Web Services) technologies. This role offers an exciting opportunity to work on diverse projects, collaborating with cross-functional teams to design, build, and optimize data pipelines and infrastructure.

Responsibilities:

* Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.

* Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.

* Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.

* Implement data governance and security best practices to ensure compliance and data integrity.

* Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.

* Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

Requirements :

* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

* 6+ years of prior experience in data engineering, with a focus on designing and building data pipelines.

* Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.

* Strong programming skills in languages such as Python, Java, or Scala.

* Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.

* Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.

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)

Strong Senior Developer – PL/SQL, SQL & ETL (Microsoft SSIS) Profile

2

Mandatory (Experience 1) – Must have minimum 5+ years of strong hands-on experience in PL/SQL and SQL development, including complex stored procedures, functions, queries, joins, data manipulation, and query/performance optimization.

3

Mandatory (Experience 2) – Must have strong hands-on experience in ETL development using Microsoft SSIS, including building, maintaining, optimizing, and troubleshooting SSIS packages for large-volume data movement and transformation.

4

Mandatory (Experience 3) – Must have solid experience working with Data Warehousing concepts and architectures, including data models, fact/dimension structures, ETL data flows, and enterprise reporting/data warehouse environments.

5

Mandatory (Experience 4) – Must have experience managing batch jobs, scheduling, and data pipelines, ensuring timely and reliable execution of enterprise ETL workflows.

6

Mandatory (Experience 5) – Must have hands-on experience in production support for SSIS/ETL and data warehouse jobs, including monitoring job execution, troubleshooting failures, performing root cause analysis, and implementing preventive fixes.

7

Mandatory (Experience 6) – Must have experience with data quality, validation, and troubleshooting, including identifying and resolving data discrepancies/issues affecting downstream reports, dashboards, and analytics.

8

Mandatory (Experience 7) – Must have experience with unit, integration, and regression testing of SQL, PL/SQL, and ETL components, along with strong documentation of technical designs, data mappings, data flows, and deployment processes.

9

Mandatory (Location) – Must be willing to work in a hybrid model from a city where Cognizant has an office.

10

Mandatory (Notice Period) – Immediate joiners or candidates who can join within 2–4 weeks.

• Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
• Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
• Work with cloud platforms GCP, Azure to manage data infrastructure.
• GCP as mandatory skills
• Collaborate with analytics and product teams to understand data needs and deliver solutions.
• Ensure data quality, reliability, security, and compliance across all data systems.
• Mentor junior data engineers and contribute to best practices and code reviews.
• Monitor and troubleshoot data pipeline performance and resolve data-related issues.
• Automate data validation, monitoring, and alerting processes.
• 8+ years of experience in data engineering or software engineering with a data focus.
• Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
• Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
• Strong understanding of data modeling, data lakes, and ETL/ELT design.
• Hands-on experience with orchestration tools like Airflow, dbt, or similar.
• Solid experience with cloud data platforms (AWS/GCP/Azure).
• Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
• Experience working in a DevOps or DataOps environment.
• Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
• Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
• Experience supporting machine learning workflows and data science initiatives.