9+ Data engineering Jobs in Hyderabad | Data engineering Job openings in Hyderabad

Mandatory Skills- Data Engineer, client Engagement, Project Management, Project Delivery, Team Leadership, Data Governance, Quality Assurance, Business Development, Data Architecture

Additional Skills- Communication Skills, Problem Solving Skills

Job Description

This position requires someone with good problem solving, business understanding and client presence. Overall professional experience of the candidate should be above 8 years. A minimum of 5 years of experience in leading and managing a client portfolio in Data Engineering space. Should have good understanding of business operations, challenges faced, and business technology used across business functions. 

The candidate must understand the usage of traditional and modern data Engineering technologies/tools for solving business problems and help clients in their data journey. The candidate must have knowledge of emerging technologies for data management including data governance, data quality, security, data integration, processing, and provisioning. The candidate must possess required soft skills to work with teams and lead medium to large teams.

Candidate should be comfortable with taking leadership roles, in client projects, pre-sales/consulting, solutioning, business development conversations, execution on data engineering projects. 

Key Responsibilities:

Client Engagement & Relationship Management:

• Serve as the primary point of contact for clients on data engineering projects, understanding their needs, challenges, and goals.
• Develop and maintain strong client relationships, ensuring high levels of client satisfaction and repeat business.
• Translate client requirements into actionable technical solutions and project plans.

 Project Management & Delivery:

• Oversee the delivery of data engineering projects from inception to completion, ensuring projects are delivered on time, within scope, and within budget.
• Manage project resources, timelines, and risks, ensuring smooth project execution and delivery.
• Collaborate with cross-functional teams including data scientists, business analysts, and IT professionals to deliver comprehensive data solutions.

 Technical Leadership & Innovation:

• Lead the design, development, and deployment of scalable data architectures, pipelines, and processes tailored to client needs.
• Stay abreast of industry trends, technologies, and best practices, and implement them in client projects to drive innovation and competitive advantage.
• Provide technical oversight and guidance to the data engineering team, ensuring the adoption of best practices and high-quality output.

 Team Leadership & Development:

• Lead, mentor, and manage a team of data engineers, fostering a collaborative and high-performance culture.
• Provide professional development opportunities, coaching, and career growth support to team members.
• Ensure the team is equipped with the necessary skills and tools to deliver high-quality consulting services.

 Data Governance & Quality Assurance:

• Implement and oversee data governance frameworks, ensuring data integrity, security, and compliance across all client projects.
• Establish and enforce data quality standards, ensuring the reliability and accuracy of data used in client solutions.
• Business Development & Consulting:
• Support business development efforts by contributing to proposals, presenting solutions to prospective clients, and identifying opportunities for expanding client engagements.
• Provide thought leadership in data engineering, contributing to white papers, webinars, and conferences to enhance the company’s reputation in the industry.

 Experience candidates should bring

• 8 to 12 years of data engineering experience with at least 3 years in a managerial role within a consulting or professional services environment.
• Proven experience in managing multiple, complex data engineering projects simultaneously.
• Experience in leading a team of 8 to 12 professionals.
• Strong problem-solving skills and the ability to handle complex, ambiguous situations.
• Exceptional project management skills, with experience in Agile methodologies.
• A client-service mindset and a desire to take on tough and challenging projects
• Effective communication skills, both written and verbal
• Ability to work effectively across functions and levels; comfort collaborating with teammates in a virtual environment.

Required Qualification

Bachelor of Engineering - Bachelor of Technology (B.E./B.Tech.) 

Role Overview

We are looking for a Tech Lead with a strong background in fintech, especially with experience or a strong interest in fraud prevention and Anti-Money Laundering (AML) technologies. 

This role is critical in leading our fintech product development, ensuring the integration of robust security measures, and guiding our team in Hyderabad towards delivering high-quality, secure, and compliant software solutions.

Responsibilities

• Lead the development of fintech solutions, focusing on fraud prevention and AML, using Typescript, ReactJs, Python, and SQL databases.
• Architect and deploy secure, scalable applications on AWS or Azure, adhering to the best practices in financial security and data protection.
• Design and manage databases with an emphasis on security, integrity, and performance, ensuring compliance with fintech regulatory standards.
• Guide and mentor the development team, promoting a culture of excellence, innovation, and continuous learning in the fintech space.
• Collaborate with stakeholders across the company, including product management, design, and QA, to ensure project alignment with business goals and regulatory requirements.
• Keep abreast of the latest trends and technologies in fintech, fraud prevention, and AML, applying this knowledge to drive the company's objectives.

Requirements

• 5-7 years of experience in software development, with a focus on fintech solutions and a strong understanding of fraud prevention and AML strategies.
• Expertise in Typescript, ReactJs, and familiarity with Python.
• Proven experience with SQL databases and cloud services (AWS or Azure), with certifications in these areas being a plus.
• Demonstrated ability to design and implement secure, high-performance software architectures in the fintech domain.
• Exceptional leadership and communication skills, with the ability to inspire and lead a team towards achieving excellence.
• A bachelor's degree in Computer Science, Engineering, or a related field, with additional certifications in fintech, security, or compliance being highly regarded.

Why Join Us?

• Opportunity to be at the cutting edge of fintech innovation, particularly in fraud prevention and AML.
• Contribute to a company with ambitious goals to revolutionize software development and make a historical impact.
• Be part of a visionary team dedicated to creating a lasting legacy in the tech industry.
• Work in an environment that values innovation, leadership, and the long-term success of its employees.

AWS Data Engineer:

Job Description

• 3+ years of experience in AWS Data Engineering.

• Design and build ETL pipelines & Data lakes to automate ingestion of structured and unstructured data

• Experience working with AWS big data technologies (Redshift, S3, AWS Glue, Kinesis, Athena ,DMS, EMR and Lambda for Serverless ETL)

• Should have knowledge in SQL and NoSQL programming languages.

• Have worked on batch and real time pipelines.

• Excellent programming and debugging skills in Scala or Python & Spark.

• Good Experience in Data Lake formation, Apache spark, python, hands on experience in deploying the models.

• Must have experience in Production migration Process

• Nice to have experience with Power BI visualization tools and connectivity

Roles & Responsibilities:

• Design, build and operationalize large scale enterprise data solutions and applications

• Analyze, re-architect and re-platform on premise data warehouses to data platforms on AWS cloud.

• Design and build production data pipelines from ingestion to consumption within AWS big data architecture, using Python, or Scala.

• Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud.

• Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
• Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
• Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
• Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
• Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
• Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree  and Random forest Algorithms.
• PolyBase queries for exporting and importing data into Azure Data Lake.
• Building data models both tabular and multidimensional using SQL Server data tools.
• Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
• Programming experience using python libraries NumPy, Pandas and Matplotlib.
• Implementing NOSQL databases and writing queries using cypher.
• Designing end user visualizations using Power BI, QlikView and Tableau.
• Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
• Experience using the expression languages MDX and DAX.
• Experience in migrating on-premise SQL server database to Microsoft Azure.
• Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
• Performance tuning complex SQL queries, hands on experience using SQL Extended events.
• Data modeling using Power BI for Adhoc reporting.
• Raw data load automation using T-SQL and SSIS
• Expert in migrating existing on-premise database to SQL Azure.
• Experience in using U-SQL for Azure Data Lake Analytics.
• Hands on experience in generating SSRS reports using MDX.
• Experience in designing predictive models using Python and SQL Server.
• Developing machine learning models using Azure Databricks and SQL Server

SpringML is looking to hire a top-notch Senior  Data Engineer who is passionate about working with data and using the latest distributed framework to process large dataset. As an Associate Data Engineer, your primary role will be to design and build data pipelines. You will be focused on helping client projects on data integration, data prep and implementing machine learning on datasets. In this role, you will work on some of the latest technologies, collaborate with partners on early win, consultative approach with clients, interact daily with executive leadership, and help build a great company. Chosen team members will be part of the core team and play a critical role in scaling up our emerging practice.

RESPONSIBILITIES:

• Ability to work as a member of a team assigned to design and implement data integration solutions.
• Build Data pipelines using standard frameworks in Hadoop, Apache Beam and other open-source solutions.
• Learn quickly – ability to understand and rapidly comprehend new areas – functional and technical – and apply detailed and critical thinking to customer solutions.
• Propose design solutions and recommend best practices for large scale data analysis

SKILLS:

• B.tech  degree in computer science, mathematics or other relevant fields.
• 4+years of experience in ETL, Data Warehouse, Visualization and building data pipelines.
• Strong Programming skills – experience and expertise in one of the following: Java, Python, Scala, C.
• Proficient in big data/distributed computing frameworks such as Apache,Spark, Kafka,
• Experience with Agile implementation methodologies

• Total Experience of 7-10 years and should be interested in teaching and research
• 3+ years’ experience in data engineering which includes data ingestion, preparation, provisioning, automated testing, and quality checks.
• 3+ Hands-on experience in Big Data cloud platforms like AWS and GCP, Data Lakes and Data Warehouses
• 3+ years of Big Data and Analytics Technologies. Experience in SQL, writing code in spark engine using python, scala or java Language. Experience in Spark, Scala
• Experience in designing, building, and maintaining ETL systems
• Experience in data pipeline and workflow management tools like Airflow
• Application Development background along with knowledge of Analytics libraries, opensource Natural Language Processing, statistical and big data computing libraries
• Familiarity with Visualization and Reporting Tools like Tableau, Kibana.
• Should be good at storytelling in Technology