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Job Description: Data Engineer
Location: Ahmedabad
Experience: 1+
Employment Type: Full-Time
We are looking for a highly motivated and experienced Data Engineer to join our team. As a Data Engineer, you will play a critical role in designing, building, and optimizing data pipelines that ensure the availability, reliability, and performance of our data infrastructure. You will collaborate closely with data scientists, analysts, and cross-functional teams to provide timely and efficient data solutions.
Responsibilities
● Design and optimize data pipelines for various data sources
● Design and implement efficient data storage and retrieval mechanisms
● Develop data modelling solutions and data validation mechanisms
● Troubleshoot data-related issues and recommend process improvements
● Collaborate with data scientists and stakeholders to provide data-driven insights and solutions
● Coach and mentor junior data engineers in the team
Skills Required:
● Minimum 1 year of experience in data engineering or related field
● Proficient in designing and optimizing data pipelines and data modeling
● Strong programming expertise in Python
● Hands-on experience with big data technologies such as Hadoop, Spark, and Hive
● Extensive experience with cloud data services such as AWS, Azure, and GCP
● Advanced knowledge of database technologies like SQL, NoSQL, and data warehousing
● Knowledge of distributed computing and storage systems
● Familiarity with DevOps practices and power automate and Microsoft Fabric will be an added advantage
● Strong analytical and problem-solving skills with outstanding communication and collaboration abilities
Qualifications
Bachelor's degree in Computer Science, Data Science, or a Computer related field

Job Description:
- 4+ years of experience in a Data Engineer role,
- Experience with object-oriented/object function scripting languages: Python, Scala, Golang, Java, etc.
- Experience with Big data tools such as Spark, Hadoop/ Kafka/ Airflow/Hive
- Experience with Streaming data: Spark/Kinesis/Kafka/Pubsub/Event Hub
- Experience with GCP/Azure data factory/AWS
- Strong in SQL Scripting
- Experience with ETL tools
- Knowledge of Snowflake Data Warehouse
- Knowledge of Orchestration frameworks: Airflow/Luig
- Good to have knowledge of Data Quality Management frameworks
- Good to have knowledge of Master Data Management
- Self-learning abilities are a must
- Familiarity with upcoming new technologies is a strong plus.
- Should have a bachelor's degree in big data analytics, computer engineering, or a related field
Personal Competency:
- Strong communication skills is a MUST
- Self-motivated, detail-oriented
- Strong organizational skills
- Ability to prioritize workloads and meet deadlines

🚀 We Are Hiring: Data Engineer | 4+ Years Experience 🚀
Job description
🔍 Job Title: Data Engineer
📍 Location: Ahmedabad
🚀 Work Mode: On-Site Opportunity
📅 Experience: 4+ Years
🕒 Employment Type: Full-Time
⏱️ Availability : Immediate Joiner Preferred
Join Our Team as a Data Engineer
We are seeking a passionate and experienced Data Engineer to be a part of our dynamic and forward-thinking team in Ahmedabad. This is an exciting opportunity for someone who thrives on transforming raw data into powerful insights and building scalable, high-performance data infrastructure.
As a Data Engineer, you will work closely with data scientists, analysts, and cross-functional teams to design robust data pipelines, optimize data systems, and enable data-driven decision-making across the organization.
Your Key Responsibilities
Architect, build, and maintain scalable and reliable data pipelines from diverse data sources.
Design effective data storage, retrieval mechanisms, and data models to support analytics and business needs.
Implement data validation, transformation, and quality monitoring processes.
Collaborate with cross-functional teams to deliver impactful, data-driven solutions.
Proactively identify bottlenecks and optimize existing workflows and processes.
Provide guidance and mentorship to junior engineers in the team.
Skills & Expertise We’re Looking For
3+ years of hands-on experience in Data Engineering or related roles.
Strong expertise in Python and data pipeline design.
Experience working with Big Data tools like Hadoop, Spark, Hive.
Proficiency with SQL, NoSQL databases, and data warehousing solutions.
Solid experience in cloud platforms - Azure
Familiar with distributed computing, data modeling, and performance tuning.
Understanding of DevOps, Power Automate, and Microsoft Fabric is a plus.
Strong analytical thinking, collaboration skills, Excellent Communication Skill and the ability to work independently or as part of a team.
Qualifications
Bachelor’s degree in Computer Science, Data Science, or a related field.
Technical Skills:
- Ability to understand and translate business requirements into design.
- Proficient in AWS infrastructure components such as S3, IAM, VPC, EC2, and Redshift.
- Experience in creating ETL jobs using Python/PySpark.
- Proficiency in creating AWS Lambda functions for event-based jobs.
- Knowledge of automating ETL processes using AWS Step Functions.
- Competence in building data warehouses and loading data into them.
Responsibilities:
- Understand business requirements and translate them into design.
- Assess AWS infrastructure needs for development work.
- Develop ETL jobs using Python/PySpark to meet requirements.
- Implement AWS Lambda for event-based tasks.
- Automate ETL processes using AWS Step Functions.
- Build data warehouses and manage data loading.
- Engage with customers and stakeholders to articulate the benefits of proposed solutions and frameworks.

consulting & implementation services in the area of Oil & Gas, Mining and Manufacturing Industry

- Data Engineer
Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON
Mandatory Requirements
- Experience in AWS Glue
- Experience in Apache Parquet
- Proficient in AWS S3 and data lake
- Knowledge of Snowflake
- Understanding of file-based ingestion best practices.
- Scripting language - Python & pyspark
CORE RESPONSIBILITIES
- Create and manage cloud resources in AWS
- Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
- Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
- Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
- Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
- Define process improvement opportunities to optimize data collection, insights and displays.
- Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
- Identify and interpret trends and patterns from complex data sets
- Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
- Key participant in regular Scrum ceremonies with the agile teams
- Proficient at developing queries, writing reports and presenting findings
- Mentor junior members and bring best industry practices
QUALIFICATIONS
- 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
- Strong background in math, statistics, computer science, data science or related discipline
- Advanced knowledge one of language: Java, Scala, Python, C#
- Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
- Proficient with
- Data mining/programming tools (e.g. SAS, SQL, R, Python)
- Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
- Data visualization (e.g. Tableau, Looker, MicroStrategy)
- Comfortable learning about and deploying new technologies and tools.
- Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
- Good written and oral communication skills and ability to present results to non-technical audiences
- Knowledge of business intelligence and analytical tools, technologies and techniques.
Familiarity and experience in the following is a plus:
- AWS certification
- Spark Streaming
- Kafka Streaming / Kafka Connect
- ELK Stack
- Cassandra / MongoDB
- CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Data Engineer
Mandatory Requirements
- Experience in AWS Glue
- Experience in Apache Parquet
- Proficient in AWS S3 and data lake
- Knowledge of Snowflake
- Understanding of file-based ingestion best practices.
- Scripting language - Python & pyspark
CORE RESPONSIBILITIES
- Create and manage cloud resources in AWS
- Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
- Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
- Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
- Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
- Define process improvement opportunities to optimize data collection, insights and displays.
- Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
- Identify and interpret trends and patterns from complex data sets
- Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
- Key participant in regular Scrum ceremonies with the agile teams
- Proficient at developing queries, writing reports and presenting findings
- Mentor junior members and bring best industry practices
QUALIFICATIONS
- 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
- Strong background in math, statistics, computer science, data science or related discipline
- Advanced knowledge one of language: Java, Scala, Python, C#
- Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
- Proficient with
- Data mining/programming tools (e.g. SAS, SQL, R, Python)
- Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
- Data visualization (e.g. Tableau, Looker, MicroStrategy)
- Comfortable learning about and deploying new technologies and tools.
- Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
- Good written and oral communication skills and ability to present results to non-technical audiences
- Knowledge of business intelligence and analytical tools, technologies and techniques.
Familiarity and experience in the following is a plus:
- AWS certification
- Spark Streaming
- Kafka Streaming / Kafka Connect
- ELK Stack
- Cassandra / MongoDB
- CI/CD: Jenkins, GitLab, Jira, Confluence other related tools